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* Alphabetized courses.

* Corrected a course name.

* Minor formatting fixes.
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@ -56,14 +56,14 @@ Courses
- This course is an introduction to the Internet architecture. We will focus on the concepts and fundamental design principles that have contributed to the Internet's scalability and robustness and survey the various protocols and algorithms used within this architecture. Topics include layering, addressing, intradomain routing, interdomain routing, reliable delivery, congestion control, and the core protocols (e.g., TCP, UDP, IP, DNS, and HTTP) and network technologies (e.g., Ethernet, wireless).
- [Lecture Notes & Assignments](https://inst.eecs.berkeley.edu/~cs168/fa14/class.html)
- [Discussion Notes](https://inst.eecs.berkeley.edu/~cs168/fa14/)
- [CS 186](https://sites.google.com/site/cs186spring2015/) **Introduction to Database Systems** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- In the project assignments in CS186, you will write a basic database management system called SimpleDB. For this project, you will focus on implementing the core modules required to access stored data on disk; in future projects, you will add support for various query processing operators, as well as transactions, locking, and concurrent queries.
- [Lecture Notes](https://sites.google.com/site/cs186fall2013/section-notes)
- [Projects](https://sites.google.com/site/cs186fall2013/homeworks)
- [CS 179](http://courses.cms.caltech.edu/cs179/) **GPU Programming** *Caltech* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This course will cover programming techniques for the GPU. The course will introduce NVIDIA's parallel computing language, CUDA. Beyond covering the CUDA programming model and syntax, the course will also discuss GPU architecture, high performance computing on GPUs, parallel algorithms, CUDA libraries, and applications of GPU computing.
- [Assignments](http://courses.cms.caltech.edu/cs179/)
- [Lecture Notes](http://courses.cms.caltech.edu/cs179/)
- [CS 186](https://sites.google.com/site/cs186spring2015/) **Introduction to Database Systems** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- In the project assignments in CS186, you will write a basic database management system called SimpleDB. For this project, you will focus on implementing the core modules required to access stored data on disk; in future projects, you will add support for various query processing operators, as well as transactions, locking, and concurrent queries.
- [Lecture Notes](https://sites.google.com/site/cs186fall2013/section-notes)
- [Projects](https://sites.google.com/site/cs186fall2013/homeworks)
- [CS 241](https://courses.engr.illinois.edu/cs241/fa2014/index.html) **Systems Programming (Fall 2014)** *Univ of Illinois, Urbana-Champaign* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- System programming refers to writing code that tasks advantage of operating system support for programmers. This course is designed to introduce you to system programming. By the end of this course, you should be proficient at writing programs that take full advantage of operating system support. To be concrete, we need to fix an operating system and we need to choose a programming language for writing programs. We chose the C language running on a Linux/UNIX operating system (which implements the POSIX standard interface between the programmer and the OS).
- [Assignments](https://courses.engr.illinois.edu/cs241/fa2014/mp.html)
@ -103,6 +103,11 @@ Courses
- [Assignments](http://comp.uark.edu/~wingning/csce3613/Homework3613.html)
- [Lecture Notes](http://comp.uark.edu/~wingning/csce3613/CourseNote3613.html)
- [Readings](http://comp.uark.edu/~wingning/csce3613/Link3613.html)
- [CSCI-UA.0202: Operating Systems (Undergrad)](http://www.cs.nyu.edu/~mwalfish/classes/15sp/index.html) **Operating Systems** *NYU* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- NYU's operating system course. It's a fundamental course focusing basic ideas of operating systems, including memory management, process shceduling, file system, ect. It also includes some recomended reading materials. What's more, there are a series of hands-on lab materials, helping you easily understand OS.
- [Assignments](http://www.cs.nyu.edu/~mwalfish/classes/15sp/labs.html)
- [Lectures](http://www.cs.nyu.edu/~mwalfish/classes/15sp/syllabus.html)
- [Old Exams](http://www.cs.nyu.edu/~mwalfish/classes/15sp/exams.html)
- [CSCI 360](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci360/csci360_f14.php) **Computer Architecture 3** *CUNY Hunter College* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- A course that covers cache design, buses, memory hierarchies, processor-peripheral interfaces, and multiprocessors, including GPUs.
- [CSCI 493.66](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci493.66/csci493.66_spr12.php) **UNIX System Programming (formerly UNIX Tools)** *CUNY Hunter College* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
@ -111,6 +116,15 @@ Courses
- [CSCI 493.75](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci493.65/csci493.65_spr14.php) **Parallel Computing** *CUNY Hunter College* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
<img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The course is an introduction to parallel algorithms and parallel programming in C and C++, using the Message Passing Interface (MPI) and the OpenMP application programming interface. It also includes a brief introduction to parallel architectures and interconnection networks. It is both theoretical and practical, including material on design methodology, performance analysis, and mathematical concepts, as well as details on programming using MPI and OpenMP.
- [CSE 421/521 Spring 2016:ops-class.org](https://www.ops-class.org/courses/buffalo/CSE421_Spring2016/) **Introduction to Operating Systems** *SUNY University at Buffalo, NY* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This course is an introduction to operating system design and implementation. We study operating systems because they are examples of mature and elegant solutions to a difficult design problem: how to safely and efficiently share system resources and provide abstractions useful to applications.
- For the processor, memory, and disks, we discuss how the operating system allocates each resource and explore the design and implementation of related abstractions. We also establish techniques for testing and improving system performance and introduce the idea of hardware virtualization. Programming assignments provide hands-on experience with implementing core operating system components in a realistic development environment. Course by [Dr.Geoffrey Challen](https://blue.cse.buffalo.edu/people/gwa/)
- [Syllabus](https://www.ops-class.org/courses/buffalo/CSE421_Spring2016/)
- [Slides](https://www.ops-class.org/slides/)
- [Video lectures](https://www.youtube.com/playlist?list=PLE6LEE8y2Jp-kbEcVR2W3vfx0Pdca0BD3)
- [Assignments](https://www.ops-class.org/asst/0/)
- [Old Exams](https://www.ops-class.org/exams/)
- [ECE 459](http://patricklam.ca/p4p/) **Programming for Performance** *University of Waterloo* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
<img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- Learn techniques for profiling, rearchitecting, and implementing software systems that can handle industrial-sized inputs, and to design and build critical software infrastructure. Learn performance optimization through parallelization, multithreading, async I/O, vectorization and GPU programming, and distributed computing.
@ -125,6 +139,11 @@ Courses
- [Assignments and Solutions](http://dcg.ethz.ch/lectures/podc_allstars/)
- [SPAC](http://homes.cs.washington.edu/~djg/teachingMaterials/spac/) **Parallelism and Concurrency** *Univ of Washington* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Technically not a course nevertheless an awesome collection of materials used by Prof Dan Grossman to teach parallelism and concurrency concepts to sophomores at UWash
- [VU:Distributed Systems](http://www.distributed-systems.net/index.php?id=distributed-systems-principles-and-paradigms) **Distributed Systems: Principles and Paradigms (Fall 2012)** *Vrije Universiteit, Amsterdam* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Distributed systems often appear to be highly complex and intertwined networked systems. Touching one component often affects many others in surprising ways. In this course, we aim at explaining the basics of distributed systems by systematically taking different perspectives, and subsequently bringing these perspectives together by looking at often-applied organizations of distributed systems. This course closely follows the timeless classic <b>Distributed Systems: Principles and Paradigms</b> by some of the pioneers in the field of Distributes systems-Andrew S. Tanenbaum and Maarten van Steen
- [Slides](http://www.distributed-systems.net/courses/ds/ds-slides/)
- [Video lectures](http://www.distributed-systems.net/courses/ds/ds-screencasts/)
- [Exams](http://www.distributed-systems.net/courses/ds/ds-exams/)
- [6.824](http://css.csail.mit.edu/6.824/2014/index.html) **Distributed Systems** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- MIT's graduate-level DS course with a focus on fault tolerance, replication, and consistency, all taught via awesome lab assignments in Golang!
- [Assignments](http://css.csail.mit.edu/6.824/2014/labs/) - Just do `git clone git://g.csail.mit.edu/6.824-golabs-2014 6.824`
@ -162,27 +181,6 @@ Courses
- [Lectures and Recitation](http://www.ece.cmu.edu/~ece447/s14/doku.php?id=schedule)
- [Homeworks](http://www.ece.cmu.edu/~ece447/s14/doku.php?id=homeworks) 7 HWs with answer set as well
- [Readings] (http://www.ece.cmu.edu/~ece447/s14/doku.php?id=readings)
- [VU:Distributed Systems](http://www.distributed-systems.net/index.php?id=distributed-systems-principles-and-paradigms) **Distributed Systems: Principles and Paradigms (Fall 2012)** *Vrije Universiteit, Amsterdam* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Distributed systems often appear to be highly complex and intertwined networked systems. Touching one component often affects many others in surprising ways. In this course, we aim at explaining the basics of distributed systems by systematically taking different perspectives, and subsequently bringing these perspectives together by looking at often-applied organizations of distributed systems. This course closely follows the timeless classic <b>Distributed Systems: Principles and Paradigms</b> by some of the pioneers in the field of Distributes systems-Andrew S. Tanenbaum and Maarten van Steen
- [Slides](http://www.distributed-systems.net/courses/ds/ds-slides/)
- [Video lectures](http://www.distributed-systems.net/courses/ds/ds-screencasts/)
- [Exams](http://www.distributed-systems.net/courses/ds/ds-exams/)
- [CSE 421/521 Spring 2016:ops-class.org](https://www.ops-class.org/courses/buffalo/CSE421_Spring2016/) **Introduction to Operating Systems** *SUNY University at Buffalo, NY* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This course is an introduction to operating system design and implementation. We study operating systems because they are examples of mature and elegant solutions to a difficult design problem: how to safely and efficiently share system resources and provide abstractions useful to applications.
- For the processor, memory, and disks, we discuss how the operating system allocates each resource and explore the design and implementation of related abstractions. We also establish techniques for testing and improving system performance and introduce the idea of hardware virtualization. Programming assignments provide hands-on experience with implementing core operating system components in a realistic development environment. Course by [Dr.Geoffrey Challen](https://blue.cse.buffalo.edu/people/gwa/)
- [Syllabus](https://www.ops-class.org/courses/buffalo/CSE421_Spring2016/)
- [Slides](https://www.ops-class.org/slides/)
- [Video lectures](https://www.youtube.com/playlist?list=PLE6LEE8y2Jp-kbEcVR2W3vfx0Pdca0BD3)
- [Assignments](https://www.ops-class.org/asst/0/)
- [Old Exams](https://www.ops-class.org/exams/)
- [CSCI-UA.0202: Operating Systems (Undergrad)](http://www.cs.nyu.edu/~mwalfish/classes/15sp/index.html) **Operating Systems** *NYU* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- NYU's operating system course. It's a fundamental course focusing basic ideas of operating systems, including memory management, process shceduling, file system, ect. It also includes some recomended reading materials. What's more, there are a series of hands-on lab materials, helping you easily understand OS.
- [Assignments](http://www.cs.nyu.edu/~mwalfish/classes/15sp/labs.html)
- [Lectures](http://www.cs.nyu.edu/~mwalfish/classes/15sp/syllabus.html)
- [Old Exams](http://www.cs.nyu.edu/~mwalfish/classes/15sp/exams.html)
-------
@ -198,7 +196,7 @@ Courses
- [Clojure](http://mooc.cs.helsinki.fi/clojure) **Functional Programming with Clojure** *University of Helsinki* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- The course is an introduction to functional programming with a dynamically typed language Clojure. We start with an introduction to Clojure; its syntax and development environment. Clojure has a good selection of data structures and we cover most of them. We also go through the basics of recursion and higher-order functions. The course material is in English.
- [Github Page](http://iloveponies.github.io/120-hour-epic-sax-marathon/index.html)
- [CMSC430](http://www.cs.umd.edu/class/spring2015/cmsc430/) **Introduction to Compilers** *Univ of Maryland* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- [CMSC 430](http://www.cs.umd.edu/class/spring2015/cmsc430/) **Introduction to Compilers** *Univ of Maryland* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The goal of CMSC 430 is to arm students with the ability to design, implement, and extend a programming language. Throughout the course, students will design and implement several related languages, and will explore parsing, syntax querying, dataflow analysis, compilation to bytecode, type systems, and language interoperation.
- [Lecture Notes](http://www.cs.umd.edu/class/spring2015/cmsc430/Schedule.html)
- [Assignments](http://www.cs.umd.edu/class/spring2015/cmsc430/Projects.html)
@ -206,6 +204,13 @@ Courses
- Covers functional programming concepts like closures, tail-call recursion & parallelism using the OCaml programming language
- [Lectures](http://www.cs.princeton.edu/~dpw/courses/cos326-12/lectures.php)
- [Assignments](http://www.cs.princeton.edu/~dpw/courses/cos326-12/assignments.php)
- [CS 143](https://web.stanford.edu/class/cs143/) **Compiler construction** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- CS143 is a Stanford's course in the practical and theoretical aspects of compiler construction.
- [Home](https://web.stanford.edu/class/cs143/)
- [Syllabus](https://web.stanford.edu/class/cs143/schedule.html)
- [Lectures](https://web.stanford.edu/class/cs143/)
- [Assignments](https://web.stanford.edu/class/cs143/)
- [CS143 - 2011](http://www.keithschwarz.com/cs143/WWW/sum2011/)
- [CS 164](https://sites.google.com/a/bodik.org/cs164/home) **Hack your language!** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Introduction to programming languages by designing and implementing domain-specific languages.
- [Lecture Videos](https://www.youtube.com/playlist?list=PL3A16CFC42CA6EF4F)
@ -214,6 +219,10 @@ Courses
- Course by Prof. Krishnamurthi (author of [HtDP](http://htdp.org/2003-09-26/Book/)) and numerous other [awesome](http://cs.brown.edu/courses/cs173/2012/book/) [books](http://papl.cs.brown.edu/2014/index.html) on programming languages. Uses a custom designed [Pyret](http://www.pyret.org/) programming language to teach the concepts. There was an [online class](http://cs.brown.edu/courses/cs173/2012/OnLine/) hosted in 2012, which includes all lecture videos for you to enjoy.
- [Videos](http://cs.brown.edu/courses/cs173/2012/Videos/)
- [Assignments](http://cs.brown.edu/courses/cs173/2014/assignments.html)
- [CS 223](https://www.classes.cs.uchicago.edu/archive/2015/winter/22300-1/) **Purely Functional Data Structures In Elm** *University of Chicago* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This course teaches functional reactive programming and purely functional data structures based on Chris Okazaki's book and using the Elm programming language.
- [Lectures](https://www.classes.cs.uchicago.edu/archive/2015/winter/22300-1/Schedule.html)
- [Assignments](https://www.classes.cs.uchicago.edu/archive/2015/winter/22300-1/Schedule.html)
- [CS 240h](http://www.scs.stanford.edu/14sp-cs240h/) **Functional Systems in Haskell** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Building software systems in Haskell
- [Lecture Slides](http://www.scs.stanford.edu/14sp-cs240h/slides/)
@ -224,10 +233,6 @@ Courses
- [Videos](http://recordings.engineering.illinois.edu/ess/portal/section/631edaeb-2a33-4537-b7c8-0c1cba783a4f)
- [Assignments](https://courses.engr.illinois.edu/cs421/fa2014/mps/index.html)
- [Exams](https://courses.engr.illinois.edu/cs421/fa2014/exams/index.html)
- [CS223](https://www.classes.cs.uchicago.edu/archive/2015/winter/22300-1/) **Purely Functional Data Structures In Elm** *University of Chicago* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This course teaches functional reactive programming and purely functional data structures based on Chris Okazaki's book and using the Elm programming language.
- [Lectures](https://www.classes.cs.uchicago.edu/archive/2015/winter/22300-1/Schedule.html)
- [Assignments](https://www.classes.cs.uchicago.edu/archive/2015/winter/22300-1/Schedule.html)
- [CS 3110](http://www.cs.cornell.edu/Courses/cs3110/2014fa/course_info.php) **Data Structures and Functional Programming** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Another course that uses OCaml to teach alternative programming paradigms, especially functional and concurrent programming.
- [Lecture Slides](http://www.cs.cornell.edu/Courses/cs3110/2014fa/lecture_notes.php)
@ -264,6 +269,8 @@ Courses
- Types and Semantics is about designing and understand programming languages, whether they be domain specific or general purpose. The goal of this class is to provide a variety of tools for designing custom (programming) languages for whatever task is at hand. Part of that will be a variety of insights on how languages work along with experiences from working with academics and industry on creating new languages such as Ceylon and Kotlin. The class focuses on types and semantics and the interplay between them. This means category theory and constructive type theory (e.g. Coq and richer variations) are ancillary topics of the class. The class also covers unconventional semantic domains such as classical linear type theory in order to both break students from convential thinking and to provide powerful targets capable of formalizing thinks like networking protocols, resource-sensitive computation, and concurrency constructs. The class project is to design and formalize a (programming) language for a purpose of the student's choosing, and assignments are designed to ensure students have had a chance to practice applying the techniques learned in class before culminating these skills in the class project.
- [Syllabus](http://www.cs.cornell.edu/courses/CS6118/2012fa/)
- [Lectures](http://www.cs.cornell.edu/courses/CS6118/2012fa/)
- [CSC 253](http://pgbovine.net/cpython-internals.htm) **CPython internals: A ten-hour codewalk through the Python interpreter source code** *University of Rochester* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Nine lectures walking through the internals of CPython, the canonical Python interpreter implemented in C. They were from the *Dynamic Languages and Software Development* course taught in Fall 2014 at the University of Rochester.
- [CSE 341](http://courses.cs.washington.edu/courses/cse341/14sp/) **Programming Languages** *University of Washington* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Covers non-imperative paradigms and languages such as Ruby, Racket, and ML and the fundamentals of programming languages.
- [Lectures](https://courses.cs.washington.edu/courses/cse341/14sp/#lecture)
@ -276,21 +283,12 @@ Courses
- A course that teaches discrete maths concepts with functional programming
- [Lecture Videos](http://cs.wheaton.edu/~tvandrun/dmfp/)
- [Assignments](http://cs.wheaton.edu/~tvandrun/dmfp/source.html)
- [CSC 253](http://pgbovine.net/cpython-internals.htm) **CPython internals: A ten-hour codewalk through the Python interpreter source code** *University of Rochester* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Nine lectures walking through the internals of CPython, the canonical Python interpreter implemented in C. They were from the *Dynamic Languages and Software Development* course taught in Fall 2014 at the University of Rochester.
- [PCPP](http://www.itu.dk/people/sestoft/itu/PCPP/E2015/) **Practical Concurrent and Parallel Programming** *IT University of Copenhagen* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- In this MSc course you learn how to write correct and efficient concurrent and parallel software, primarily using Java, on standard shared-memory multicore hardware.
- The course covers basic mechanisms such as threads, locks and shared memory as well as more advanced mechanisms such as parallel streams for bulk data, transactional memory, message passing, and lock-free data structures with compare-and-swap.
- It covers concepts such as atomicity, safety, liveness and deadlock.
- It covers how to measure and understand performance and scalability of parallel programs.
- It covers tools and methods to find bugs in concurrent programs.
- [CS 143](https://web.stanford.edu/class/cs143/) **Compiler construction** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- CS143 is a Stanford's course in the practical and theoretical aspects of compiler construction.
- [Home](https://web.stanford.edu/class/cs143/)
- [Syllabus](https://web.stanford.edu/class/cs143/schedule.html)
- [Lectures](https://web.stanford.edu/class/cs143/)
- [Assignments](https://web.stanford.edu/class/cs143/)
- [CS143 - 2011](http://www.keithschwarz.com/cs143/WWW/sum2011/)
- [6.945](https://groups.csail.mit.edu/mac/users/gjs/6.945/index.html) **Adventures in Advanced Symbolic Programming** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Taught by Gerald Sussman of SICP fame, this class deals with concepts and techniques for the design an implementation of large software systems that can be adapted to uses not anticipated by the designer. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications.
- [Assignments](https://groups.csail.mit.edu/mac/users/gjs/6.945/assignments.html): Extensive programming assignments, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or other "functional" language.
@ -305,6 +303,16 @@ Courses
- [Full Lecture Materials](http://datastructur.es/sp16/) Lecture of Spring 2016. This website contains full matrials including video links, labs, homeworks, projects. Very good for self-learner. Also a good start for Java. And it includes some other usefull resources for Java Documentation, Data Structure Resources, Git/GitHub and Java Development Resources. [Resources](http://datastructur.es/sp16/resources.html)
- [Labs](http://www.cs.berkeley.edu/~jrs/61b/lab/index.html) The link to labs and projects is included in the website.
- [Lecture Videos on Youtube](http://www.youtube.com/watch?v=frxF7Vs96YU&list=PLMM0a7ZGnITrgfhOxMNP7bpP4hhhKNY9s) The link to videos is included in the website.
- [CS 97SI](http://web.stanford.edu/class/cs97si/) **Introduction to Competitive Programming** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Fantastic repository of theory and practice problems across various topics for students who are interested to participate in ACM-ICPC.
- [Lectures and Assignments](http://stanford.edu/~liszt90/acm/notebook.html)
- [CS 224](http://people.seas.harvard.edu/~minilek/cs224/fall14/index.html) **Advanced Algorithms** *Harvard University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- CS 224 is an advanced course in algorithm design, and topics we will cover include the word RAM model, data structures, amortization, online algorithms, linear programming, semidefinite programming, approximation algorithms, hashing, randomized algorithms, fast exponential time algorithms, graph algorithms, and computational geometry.
- [Lecture Videos](http://people.seas.harvard.edu/~minilek/cs224/fall14/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf))
- [Assignments](http://people.seas.harvard.edu/~minilek/cs224/fall14/hmwk.html)
- [CS 261](http://theory.stanford.edu/~tim/w16/w16.html) **A Second Course in Algorithms** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Algorithms for network optimization: max-flow, min-cost flow, matching, assignment, and min-cut problems. Introduction to linear programming. Use of LP duality for design and analysis of algorithms. Approximation algorithms for NP-complete problems such as Steiner Trees, Traveling Salesman, and scheduling problems. Randomized algorithms. Introduction to online algorithms.
- [Lecture Notes, Videos & Assignments](http://theory.stanford.edu/~tim/w16/w16.html) ([Youtube](https://www.youtube.com/playlist?list=PLEGCF-WLh2RJh2yDxlJJjnKswWdoO8gAc))
- [CS 473/573](http://web.engr.illinois.edu/~jeffe/teaching/algorithms/) **Fundamental Algorithms** *Univ of Illinois, Urbana-Champaign* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Algorithms class covering recursion, randomization, amortization, graph algorithms, network flows and hardness. The lecture notes by Prof. Erikson are comprehensive enough to be a book by themselves. Highly recommended!
- [Lecture Notes](http://web.engr.illinois.edu/~jeffe/teaching/algorithms/all-algorithms.pdf)
@ -327,31 +335,19 @@ Courses
*CUNY Hunter College*
- It is currently an intensive introduction to program development and problem solving. Its emphasis is on the process of designing, implementing, and evaluating small-scale programs. It is not supposed to be a C++ programming course, although much of the course is spent on the details of C++. C++ is an extremely large and complex programming language with many features that interact in unexpected ways. One does not need to know even half of the language to use it well.
- [Lectures and Assignments](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci135/csci135_36_fall12.php)
- [16s-4102](http://www.cs.virginia.edu/~shelat/16s-4102/) **Algorithms** *University of Virginia* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- [Lecture Videos & Homeworks](http://www.cs.virginia.edu/~shelat/16s-4102/) ([Youtube](https://www.youtube.com/channel/UCxXYk53cSZof2bR_Ax0uJYQ/videos))
- [CS 224](http://people.seas.harvard.edu/~minilek/cs224/fall14/index.html) **Advanced Algorithms** *Harvard University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- CS 224 is an advanced course in algorithm design, and topics we will cover include the word RAM model, data structures, amortization, online algorithms, linear programming, semidefinite programming, approximation algorithms, hashing, randomized algorithms, fast exponential time algorithms, graph algorithms, and computational geometry.
- [Lecture Videos](http://people.seas.harvard.edu/~minilek/cs224/fall14/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf))
- [Assignments](http://people.seas.harvard.edu/~minilek/cs224/fall14/hmwk.html)
- [CSCI 235](http://compsci.hunter.cuny.edu/~sweiss/courses/csci235.php) **Software Design and Analysis II** *CUNY Hunter College* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Introduces algorithms for a few common problems such as sorting. Practically speaking, it furthers the students' programming skills with topics such as recursion, pointers, and exception handling, and provides a chance to improve software engineering skills and to give the students practical experience for more productive programming.
- [Lectures and Assignments](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci235/csci235_f14.php)
- [CS 261](http://theory.stanford.edu/~tim/w16/w16.html) **A Second Course in Algorithms** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Algorithms for network optimization: max-flow, min-cost flow, matching, assignment, and min-cut problems. Introduction to linear programming. Use of LP duality for design and analysis of algorithms. Approximation algorithms for NP-complete problems such as Steiner Trees, Traveling Salesman, and scheduling problems. Randomized algorithms. Introduction to online algorithms.
- [Lecture Notes, Videos & Assignments](http://theory.stanford.edu/~tim/w16/w16.html) ([Youtube](https://www.youtube.com/playlist?list=PLEGCF-WLh2RJh2yDxlJJjnKswWdoO8gAc))
- [CSCI 335](http://compsci.hunter.cuny.edu/~sweiss/courses/csci335.php) **Software Design and Analysis III** <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
*CUNY Hunter College*
- This includes the introduction of hashes, heaps, various forms of trees, and graphs. It also revisits recursion and the sorting problem from a higher perspective than was presented in the prequels. On top of this, it is intended to introduce methods of algorithmic analysis.
- [Lectures and Assignments](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci335/csci335_s14.php)
- [CSE 373](http://www3.cs.stonybrook.edu/~skiena/373/) **Analysis of Algorithms** *Stony Brook University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Prof Steven Skiena's no stranger to any student when it comes to algorithms. His seminal [book](http://www.algorist.com/) has been touted by many to be best for [getting that job in Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html). In addition, he's also well-known for tutoring students in competitive [programming competitions](http://www.programming-challenges.com/pg.php?page=index). If you're looking to brush up your knowledge on Algorithms, you can't go wrong with this course.
- [Lecture Videos](http://www.cs.sunysb.edu/~algorith/video-lectures/)
- [CSE 331](http://courses.cs.washington.edu/courses/cse331/15sp/) **Software Design and Implementation** *University of Washington* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Explores concepts and techniques for design and construction of reliable and maintainable software systems in modern high-level languages; program structure and design; program-correctness approaches, including testing.
- [Lectures, Assignments, and Exams](http://courses.cs.washington.edu/courses/cse331/15sp/#all)
- [CS 97SI](http://web.stanford.edu/class/cs97si/) **Introduction to Competitive Programming** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Fantastic repository of theory and practice problems across various topics for students who are interested to participate in ACM-ICPC.
- [Lectures and Assignments](http://stanford.edu/~liszt90/acm/notebook.html)
- [CSE 373](http://www3.cs.stonybrook.edu/~skiena/373/) **Analysis of Algorithms** *Stony Brook University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Prof Steven Skiena's no stranger to any student when it comes to algorithms. His seminal [book](http://www.algorist.com/) has been touted by many to be best for [getting that job in Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html). In addition, he's also well-known for tutoring students in competitive [programming competitions](http://www.programming-challenges.com/pg.php?page=index). If you're looking to brush up your knowledge on Algorithms, you can't go wrong with this course.
- [Lecture Videos](http://www.cs.sunysb.edu/~algorith/video-lectures/)
- [ECS 122A](http://web.cs.ucdavis.edu/~gusfield/cs122f10/) **Algorithm Design and Analysis** *UC Davis* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Taught by [Dan Gusfield](http://web.cs.ucdavis.edu/~gusfield/) in 2010, this course is an undergraduate introduction to algorithm design and analysis. It features traditional topics, such as Big Oh notation, as well as an importance on implementing specific algorithms. Also featured are sorting (in linear time), graph algorithms, depth-first search, string matching, dynamic programming, NP-completeness, approximation, and randomization.
- [Syllabus](http://web.cs.ucdavis.edu/~gusfield/cs122f10/syll122.pdf)
@ -366,15 +362,6 @@ Courses
- This course taught in the MIT Independent Activities Period in 2009 goes over common solution to common interview questions for software engineer interviews at highly selective companies like Apple, Google, and Facebook. They cover time complexity, hash tables, binary search trees, and other common algorithm topics you should have already covered in a different course, but goes more in depth on things you wouldn't otherwise learn in class- like bitwise logic and problem solving tricks.
- [Handouts](http://courses.csail.mit.edu/iap/interview/materials.php)
- [Topics Covered](http://courses.csail.mit.edu/iap/interview/calendar.php)
- [6.851](http://courses.csail.mit.edu/6.851/spring14/index.html) **Advanced Data Structures** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This is an advanced DS course, you must be done with the [Advanced Algorithms](http://courses.csail.mit.edu/6.854/current/) course before attempting this one.
- [Lectures](http://courses.csail.mit.edu/6.851/spring14/lectures/) Contains videos from sp2012 version, but there isn't much difference.
- [Assignments](http://courses.csail.mit.edu/6.851/spring14/hmwk.html) contains the calendar as well.
- [6.854/18.415J](http://courses.csail.mit.edu/6.854/current/) **Advanced Algorithms** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Advanced course in algorithms by Dr. David Karger covering topics such as amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms.
- **Register** on [NB](http://nb.mit.edu/subscribe?key=D3a8CYpoO2VcR1ZcfaxmR5KbyjCGXd3INNXvL3mxEakYJ7qGJw) to access the [problem set and lectures](http://nb.mit.edu/).
- [15-451/651](http://www.cs.cmu.edu/afs/cs/academic/class/15451-f10/www/) **Algorithms** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The required algorithms class that go in depth into all basic algorithms and the proofs behind them. This is one of the heavier algorithms curriculums on this page. Taught by Avrim Blum and [Manuel Blum](http://en.wikipedia.org/wiki/Manuel_Blum) who has a Turing Award due to his contributions to algorithms. Course link includes a very comprehensive set of reference notes by Avrim Blum.
- [6.006](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/index.htm) **Introduction to Algorithms** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems. This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
- [Lecture Videos](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/)
@ -389,6 +376,13 @@ Courses
- [Assignments](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/assignments/)
- [Resources](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/download-course-materials/)
- [Old Exams](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/exams/)
- [6.851](http://courses.csail.mit.edu/6.851/spring14/index.html) **Advanced Data Structures** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This is an advanced DS course, you must be done with the [Advanced Algorithms](http://courses.csail.mit.edu/6.854/current/) course before attempting this one.
- [Lectures](http://courses.csail.mit.edu/6.851/spring14/lectures/) Contains videos from sp2012 version, but there isn't much difference.
- [Assignments](http://courses.csail.mit.edu/6.851/spring14/hmwk.html) contains the calendar as well.
- [6.854/18.415J](http://courses.csail.mit.edu/6.854/current/) **Advanced Algorithms** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Advanced course in algorithms by Dr. David Karger covering topics such as amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms.
- **Register** on [NB](http://nb.mit.edu/subscribe?key=D3a8CYpoO2VcR1ZcfaxmR5KbyjCGXd3INNXvL3mxEakYJ7qGJw) to access the [problem set and lectures](http://nb.mit.edu/).
- [6.854J/18.415J](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-854j-advanced-algorithms-fall-2005/index.htm) **Advanced Algorithms** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course is a first-year graduate course in algorithms. Emphasis is placed on fundamental algorithms and advanced methods of algorithmic design, analysis, and implementation. Techniques to be covered include amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms. Domains include string algorithms, network optimization, parallel algorithms, computational geometry, online algorithms, external memory, cache, and streaming algorithms, and data structures. The need for efficient algorithms arises in nearly every area of computer science. But the type of problem to be solved, the notion of what algorithms are "efficient,'' and even the model of computation can vary widely from area to area. In this second class in algorithms, we will survey many of the techniques that apply broadly in the design of efficient algorithms, and study their application in a wide range of application domains and computational models. The goal is for the class to be broad rather than deep. Our plan is to touch upon the following areas. This is a tentative list of topics that might be covered in the class; we will select material adaptively based on the background, interests, and rate of progress of the students.
- [Lecture Videos - Spring 2016](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c)
@ -396,6 +390,10 @@ Courses
- [Assignments](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-854j-advanced-algorithms-fall-2005/assignments/)
- [Readings](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-854j-advanced-algorithms-fall-2005/readings/)
- [Resources](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-854j-advanced-algorithms-fall-2005/download-course-materials/)
- [15-451/651](http://www.cs.cmu.edu/afs/cs/academic/class/15451-f10/www/) **Algorithms** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The required algorithms class that go in depth into all basic algorithms and the proofs behind them. This is one of the heavier algorithms curriculums on this page. Taught by Avrim Blum and [Manuel Blum](http://en.wikipedia.org/wiki/Manuel_Blum) who has a Turing Award due to his contributions to algorithms. Course link includes a very comprehensive set of reference notes by Avrim Blum.
- [16s-4102](http://www.cs.virginia.edu/~shelat/16s-4102/) **Algorithms** *University of Virginia* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- [Lecture Videos & Homeworks](http://www.cs.virginia.edu/~shelat/16s-4102/) ([Youtube](https://www.youtube.com/channel/UCxXYk53cSZof2bR_Ax0uJYQ/videos))
-------
@ -427,6 +425,16 @@ Courses
- [Syllabus](http://www.cs.cornell.edu/courses/CS3110/2014fa/course_info.php)
- [Lectures](http://www.cs.cornell.edu/courses/CS3110/2014fa/lecture_notes.php)
- [Assignments](http://www.cs.cornell.edu/courses/CS3110/2014fa/index.php)
- [CS 3220](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/) **Introduction to Scientific Computing** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- In this one-semester survey course, we introduce numerical methods for solving linear and nonlinear equations, interpolating data, computing integrals, and solving differential equations, and we describe how to use these tools wisely (we hope!) when solving scientific problems.
- [Syllabus](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/syllabus.html)
- [Lectures](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/lectures.html)
- [Assignments](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/assignments.html)
- [CS 4300](http://www.cs.cornell.edu/courses/CS4300/2013fa/) **Information Retrieval** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Studies the methods used to search for and discover information in large-scale systems. The emphasis is on information retrieval applied to textual materials, but there is some discussion of other formats.The course includes techniques for searching, browsing, and filtering information and the use of classification systems and thesauruses. The techniques are illustrated with examples from web searching and digital libraries.
- [Syllabus](http://www.cs.cornell.edu/courses/CS4300/2013fa/lectures/introduction.pdf)
- [Lectures](http://www.cs.cornell.edu/courses/CS4300/2013fa/lectures.htm)
- [Assignments](http://www.cs.cornell.edu/courses/CS4300/2013fa/lectures.htm)
- [CS 4810](http://www.cs.cornell.edu/~dsteurer/toc13/) **Introduction to Theory of Computing** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This undergraduate course provides a broad introduction to the mathematical foundations of computer science. We will examine basic computational models, especially Turing machines. The goal is to understand what problems can or cannot be solved in these models.
- [Syllabus](http://www.cs.cornell.edu/~dsteurer/toc13/syllabus/)
@ -449,16 +457,6 @@ Courses
- [Notes](http://www.csce.uark.edu/~sgauch/3193/S11/notes/index.html)
- [Assignments](http://www.csce.uark.edu/~sgauch/3193/S11/hw/index.html)
- [Practice Exams](http://www.csce.uark.edu/~sgauch/3193/S11/exams/index.html)
- [CS 3220](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/) **Introduction to Scientific Computing** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- In this one-semester survey course, we introduce numerical methods for solving linear and nonlinear equations, interpolating data, computing integrals, and solving differential equations, and we describe how to use these tools wisely (we hope!) when solving scientific problems.
- [Syllabus](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/syllabus.html)
- [Lectures](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/lectures.html)
- [Assignments](http://www.cs.cornell.edu/~bindel/class/cs3220-s12/assignments.html)
- [CS 4300](http://www.cs.cornell.edu/courses/CS4300/2013fa/) **Information Retrieval** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Studies the methods used to search for and discover information in large-scale systems. The emphasis is on information retrieval applied to textual materials, but there is some discussion of other formats.The course includes techniques for searching, browsing, and filtering information and the use of classification systems and thesauruses. The techniques are illustrated with examples from web searching and digital libraries.
- [Syllabus](http://www.cs.cornell.edu/courses/CS4300/2013fa/lectures/introduction.pdf)
- [Lectures](http://www.cs.cornell.edu/courses/CS4300/2013fa/lectures.htm)
- [Assignments](http://www.cs.cornell.edu/courses/CS4300/2013fa/lectures.htm)
- [6.045](https://stellar.mit.edu/S/course/6/sp15/6.045/index.html) **Great Ideas in Theoretical Computer Science** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power.
- [Syllabus](https://stellar.mit.edu/S/course/6/sp15/6.045/courseMaterial/topics/topic1/syllabus/syllabus2015/syllabus2015.pdf)
@ -541,6 +539,12 @@ Courses
- [Syllabus](http://www.cs.cornell.edu/courses/CS1133/2013fa/about/overview.php)
- [Lectures](http://www.cs.cornell.edu/courses/CS1133/2013fa/lectures/index.php)
- [Assignments](http://www.cs.cornell.edu/courses/CS1133/2013fa/assignments/index.php)
- [CS 1410-2](http://www.eng.utah.edu/~cs1410-20/) and [CS2420-20](http://www.eng.utah.edu/~cs2420-20/) **Computer Science I and II for Hackers** *University of Utah* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- An intro course in the spirit of SICP designed by [Professor Matthew Flatt](http://www.cs.utah.edu/~mflatt/) (one of the lead designers of Racket and author of HtDP). Mostly Racket and C, and a bit of Java, with explanations on how high level functional programming concepts relate to the design of OOP programs. Do this one before SICP if SICP is a bit too much...
- [Lectures and Assignments 1](http://www.eng.utah.edu/~cs1410-20/schedule.html)
- [Lectures and Assignments 2](http://www.eng.utah.edu/~cs2420-20/schedule.html)
- [Textbook](http://htdp.org/2003-09-26/Book/curriculum.html)
- [Racket Language](http://racket-lang.org/)
- [CS 2110](http://www.cs.cornell.edu/courses/CS2110/2014fa/index.html) **Object-Oriented Programming and Data Structures** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- CS 2110 is an intermediate-level programming course and an introduction to computer science. Topics include program design and development, debugging and testing, object-oriented programming, proofs of correctness, complexity analysis, recursion, commonly used data structures, graph algorithms, and abstract data types. Java is the principal programming language. The course syllabus can easily be extracted by looking at the link to [lectures](http://www.cs.cornell.edu/courses/CS2110/2014fa/lecturenotes.html).
- [Syllabus](http://www.cs.cornell.edu/courses/CS2110/2014fa/lecturenotes.html)
@ -557,48 +561,22 @@ Courses
- [Notes](http://www.csce.uark.edu/~sgauch/2004/S14/notes/index.html)
- [Assignments](http://www.csce.uark.edu/~sgauch/2004/S14/hw/index.html)
- [Practice Exams](http://www.csce.uark.edu/~sgauch/2004/S14/index.html)
- [CS-for-all](http://www.cs.hmc.edu/csforall/) **CS for All** *Harvey Mudd College* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This book (and course) takes a unique approach to “Intro CS.” In a nutshell, our objective is to provide an introduction to computer science as an intellectually rich and vibrant field rather than focusing exclusively on computer programming. While programming is certainly an important and pervasive element of our approach, we emphasize concepts and problem-solving over syntax and programming language features.
- [Lectures and Other resources](https://www.cs.hmc.edu/twiki/bin/view/ModularCS1)
- [6.001](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-001-structure-and-interpretation-of-computer-programs-spring-2005/index.htm) **Structure and Interpretation of Computer Programs** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Teaches big-picture computing concepts using the Scheme programming language. Students will implement programs in a variety of different programming paradigms (functional, object-oriented, logical). Heavy emphasis on function composition, code-as-data, control abstraction with continuations, and syntactic abstraction through macros. An excellent course if you are looking to build a mental framework on which to hang your programming knowledge.
- [Lectures](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-001-structure-and-interpretation-of-computer-programs-spring-2005/video-lectures)
- [Textbook](http://mitpress.mit.edu/sicp/full-text/book/book.html) ([epub](https://github.com/sarabander/sicp), [pdf](https://github.com/sarabander/sicp-pdf))
- [IDE](http://www.neilvandyke.org/racket-sicp/)
- [CS1410-2](http://www.eng.utah.edu/~cs1410-20/) and [CS2420-20](http://www.eng.utah.edu/~cs2420-20/) **Computer Science I and II for Hackers** *University of Utah* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- An intro course in the spirit of SICP designed by [Professor Matthew Flatt](http://www.cs.utah.edu/~mflatt/) (one of the lead designers of Racket and author of HtDP). Mostly Racket and C, and a bit of Java, with explanations on how high level functional programming concepts relate to the design of OOP programs. Do this one before SICP if SICP is a bit too much...
- [Lectures and Assignments 1](http://www.eng.utah.edu/~cs1410-20/schedule.html)
- [Lectures and Assignments 2](http://www.eng.utah.edu/~cs2420-20/schedule.html)
- [Textbook](http://htdp.org/2003-09-26/Book/curriculum.html)
- [Racket Language](http://racket-lang.org/)
- [CS-for-all](http://www.cs.hmc.edu/csforall/) **CS for All** *Harvey Mudd College* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This book (and course) takes a unique approach to “Intro CS.” In a nutshell, our objective is to provide an introduction to computer science as an intellectually rich and vibrant field rather than focusing exclusively on computer programming. While programming is certainly an important and pervasive element of our approach, we emphasize concepts and problem-solving over syntax and programming language features.
- [Lectures and Other resources](https://www.cs.hmc.edu/twiki/bin/view/ModularCS1)
-------
### Machine Learning
- [StatLearning](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) **Intro to Statistical Learning** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines.
- The lectures cover all the material in [An Introduction to Statistical Learning, with Applications in R](http://www-bcf.usc.edu/~gareth/ISL/) which is a more approachable version of the [Elements of Statistical Learning](http://statweb.stanford.edu/~tibs/ElemStatLearn/) (or ESL) book.
- [11-785](http://deeplearning.cs.cmu.edu/) **Deep Learning** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course presents the subject through a series of seminars and labs, which will explore it from its early beginnings, and work themselves to some of the state of the art. The seminars will cover the basics of deep learning and the underlying theory, as well as the breadth of application areas to which it has been applied, as well as the latest issues on learning from very large amounts of data. We will concentrate largely, although not entirely, on the connectionist architectures that are most commonly associated with it. *Lectures* and *Reading Notes* are available on the page.
- [10-601](http://www.cs.cmu.edu/~ninamf/courses/601sp15/) **Machine Learning** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- This course covers the theory and practical algorithms for machine learning from a variety of perspectives. It covers topics such as Bayesian networks, decision tree learning, Support Vector Machines, statistical learning methods, unsupervised learning and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC learning framework, Bayesian learning methods, margin-based learning, and Occam's Razor. Short programming assignments include hands-on experiments with various learning algorithms. This course is designed to give a graduate-level student a thorough grounding in the methodologies, technologies, mathematics and algorithms currently needed by people who do research in machine learning.
- Taught by one of the leading experts on Machine Learning - **Tom Mitchell**
- [Lectures](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml)
- [Project Ideas and Datasets](http://www.cs.cmu.edu/~tom/10701_sp11/proj.shtml)
- [10-708](http://www.cs.cmu.edu/~epxing/Class/10708-14/index.html) **Probabilistic Graphical Models** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Many of the problems in artificial intelligence, statistics, computer systems, computer vision, natural language processing, and computational biology, among many other fields, can be viewed as the search for a coherent global conclusion from local information. The probabilistic graphical models framework provides a unified view for this wide range of problems, enabling efficient inference, decision-making and learning in problems with a very large number of attributes and huge datasets. This graduate-level course will provide you with a strong foundation for both applying graphical models to complex problems and for addressing core research topics in graphical models.
- [Lecture Videos](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [Assignments](http://www.cs.cmu.edu/~epxing/Class/10708-14/homework.html)
- [Lecture notes](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [Readings](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [EE103](http://stanford.edu/class/ee103/) **Introduction to Matrix Methods** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course covers the basics of matrices and vectors, solving linear equations, least-squares methods, and many applications. It'll cover the mathematics, but the focus will be on using matrix methods in applications such as tomography, image processing, data fitting, time series prediction, finance, and many others. EE103 is based on a book that [Stephen Boyd](http://stanford.edu/~boyd/) and [Lieven Vandenberghe](http://www.seas.ucla.edu/~vandenbe/) are currently writing. Students will use a new language called [Julia](http://julialang.org/) to do computations with matrices and vectors.
- [Lectures](http://stanford.edu/class/ee103/lectures.html)
- [Book](http://stanford.edu/class/ee103/mma.html)
- [Assignments](http://stanford.edu/class/ee103/homework.html)
- [Code](http://stanford.edu/class/ee103/julia_files)
- [COMS 4771](http://www.cs.columbia.edu/~jebara/4771/index.html) **Machine Learning** *Columbia University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Course taught by [Tony Jebara](http://www.cs.columbia.edu/~jebara/resume.html) introduces topics in Machine Learning for both generative and discriminative estimation. Material will include least squares methods, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models, hidden Markov models, support vector machines, and kernel methods.
- [Lectures and Assignments](http://www.cs.columbia.edu/~jebara/4771/handouts.html)
- [CS 109](http://cs109.github.io/2015/) **Data Science** *Harvard University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Learning from data in order to gain useful predictions and insights. This course introduces methods for five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.
- [Lectures](http://cm.dce.harvard.edu/2015/01/14328/publicationListing.shtml)
@ -628,6 +606,14 @@ Courses
- The course introduces the math and algorithms underneath state-of-the-art robotic systems. The majority of these techniques are heavily based on probabilistic reasoning and optimization---two areas with wide applicability in modern Artificial Intelligence. An intended side-effect of the course is to generally strengthen your expertise in these two areas.
- [Lectures Notes](http://www.cs.berkeley.edu/~pabbeel/cs287-fa13/#syllabus)
- [Assignments](http://www.cs.berkeley.edu/~pabbeel/cs287-fa13/#assignments)
- [CS 395T](http://www.nr.com/CS395T/) **Statistical and Discrete Methods for Scientific Computing** *University of Texas* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- Practical course in applying modern statistical techniques to real data, particularly bioinformatic data and large data sets. The emphasis is on efficient computation and concise coding, mostly in MATLAB and C++.
Topics covered include probability theory and Bayesian inference; univariate distributions; Central Limit Theorem; generation of random deviates; tail (p-value) tests; multiple hypothesis correction; empirical distributions; model fitting; error estimation; contingency tables; multivariate normal distributions; phylogenetic clustering; Gaussian mixture models; EM methods; maximum likelihood estimation; Markov Chain Monte Carlo; principal component analysis; dynamic programming; hidden Markov models; performance measures for classifiers; support vector machines; Wiener filtering; wavelets; multidimensional interpolation; information theory.
- [Lectures and Assignments](http://granite.ices.utexas.edu/coursewiki/index.php/Main_Page)
- [CS 4780](http://www.cs.cornell.edu/courses/CS4780/2014fa/) **Machine Learning** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course will introduce you to technologies for building data-centric information systems on the World Wide Web, show the practical applications of such systems, and discuss their design and their social and policy context by examining cross-cutting issues such as citizen science, data journalism and open government. Course work involves lectures and readings as well as weekly homework assignments, and a semester-long project in which the students demonstrate their expertise in building data-centric Web information systems.
- [Syllabus](http://www.cs.cornell.edu/courses/CS4780/2014fa/)
- [Lectures](http://www.cs.cornell.edu/courses/CS4780/2014fa/)
- [CS 4786](http://www.cs.cornell.edu/courses/CS4786/2015sp/index.htm) **Machine Learning for Data Science** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments"/> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- An introductory course in machine learning, with a focus on data modeling and related methods and learning algorithms for data sciences. Tentative topic list:
- Dimensionality reduction, such as principal component analysis (PCA) and the singular value decomposition (SVD), canonical correlation analysis (CCA), independent component analysis (ICA), compressed sensing, random projection, the information bottleneck. (We expect to cover some, but probably not all, of these topics).
@ -636,17 +622,6 @@ Courses
- Regression will be covered if time permits.
- [Assignments](http://www.cs.cornell.edu/courses/CS4786/2015sp/assignments.htm)
- [Lectures](http://www.cs.cornell.edu/courses/CS4786/2015sp/lectures.htm)
- [CS 4780](http://www.cs.cornell.edu/courses/CS4780/2014fa/) **Machine Learning** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course will introduce you to technologies for building data-centric information systems on the World Wide Web, show the practical applications of such systems, and discuss their design and their social and policy context by examining cross-cutting issues such as citizen science, data journalism and open government. Course work involves lectures and readings as well as weekly homework assignments, and a semester-long project in which the students demonstrate their expertise in building data-centric Web information systems.
- [Syllabus](http://www.cs.cornell.edu/courses/CS4780/2014fa/)
- [Lectures](http://www.cs.cornell.edu/courses/CS4780/2014fa/)
- [COMS 4771](http://www.cs.columbia.edu/~jebara/4771/index.html) **Machine Learning** *Columbia University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Course taught by [Tony Jebara](http://www.cs.columbia.edu/~jebara/resume.html) introduces topics in Machine Learning for both generative and discriminative estimation. Material will include least squares methods, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models, hidden Markov models, support vector machines, and kernel methods.
- [Lectures and Assignments](http://www.cs.columbia.edu/~jebara/4771/handouts.html)
- [CS395T](http://www.nr.com/CS395T/) **Statistical and Discrete Methods for Scientific Computing** *University of Texas* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- Practical course in applying modern statistical techniques to real data, particularly bioinformatic data and large data sets. The emphasis is on efficient computation and concise coding, mostly in MATLAB and C++.
Topics covered include probability theory and Bayesian inference; univariate distributions; Central Limit Theorem; generation of random deviates; tail (p-value) tests; multiple hypothesis correction; empirical distributions; model fitting; error estimation; contingency tables; multivariate normal distributions; phylogenetic clustering; Gaussian mixture models; EM methods; maximum likelihood estimation; Markov Chain Monte Carlo; principal component analysis; dynamic programming; hidden Markov models; performance measures for classifiers; support vector machines; Wiener filtering; wavelets; multidimensional interpolation; information theory.
- [Lectures and Assignments](http://granite.ices.utexas.edu/coursewiki/index.php/Main_Page)
- [CVX 101](https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/info) **Convex Optimization** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
<img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course concentrates on recognizing and solving convex optimization problems that arise in applications. Topics addressed include the following. Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interior-point methods. Applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.
@ -656,58 +631,67 @@ Topics covered include probability theory and Bayesian inference; univariate dis
- This increasingly popular course is taught through the Data Science Center at NYU. Originally introduced by [Yann Lecun](http://yann.lecun.com/), it is now led by [Zaid Harchaoui](http://www.harchaoui.eu/), although Prof. Lecun is rumored to still stop by from time to time. It covers the theory, technique, and tricks that are used to achieve very high accuracy for machine learning tasks in computer vision and natural language processing. The assignments are in Lua and hosted on Kaggle.
- [Course Page](http://cilvr.cs.nyu.edu/doku.php?id=deeplearning2015:schedule)
- [Recorded Lectures](http://techtalks.tv/deep-learning-nyu-spring-2015/)
- [**Machine Learning: 2014-2015**](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) *University of Oxford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- The course focusses on neural networks and uses the [Torch](https://github.com/torch/torch7/wiki/Cheatsheet) deep learning library (implemented in Lua) for exercises and assignments. Topics include: logistic regression, back-propagation, convolutional neural networks, max-margin learning, siamese networks, recurrent neural networks, LSTMs, hand-writing with recurrent neural networks, variational autoencoders and image generation and reinforcement learning
- [Lectures and Assignments](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
- [Source code](https://github.com/oxford-cs-ml-2015/)
- [EECS E6894](http://llcao.net/cu-deeplearning15/index.html) **Deep Learning for Computer Vision and Natural Language Processing** *Columbia University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This graduate level research class focuses on deep learning techniques for vision and natural language processing problems. It gives an overview of the various deep learning models and techniques, and surveys recent advances in the related fields. This course uses Theano as the main programming tool. GPU programming experiences are preferred although not required. Frequent paper presentations and a heavy programming workload are expected.
- [Readings](http://llcao.net/cu-deeplearning15/reading.html)
- [Assignments](http://llcao.net/cu-deeplearning15/programming_problem.html)
- [Lecture Notes](http://llcao.net/cu-deeplearning15/index.html)
- [EECS E6893 & EECS E6895](http://www.ee.columbia.edu/~cylin/course/bigdata/) **Big Data Analytics & Advanced Big Data Analytics** *Columbia University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Students will gain knowledge on analyzing Big Data. It serves as an introductory course for graduate students who are expecting to face Big Data storage, processing, analysis, visualization, and application issues on both workplaces and research environments.
- Taught by [Dr. Ching-Yung Lin](http://researcher.watson.ibm.com/researcher/view.php?person=us-chingyung)
- [Course Site](http://www.ee.columbia.edu/~cylin/course/bigdata/)
- Assignments - Assignments are present in the Course Slides
- [EECS E6894](http://llcao.net/cu-deeplearning15/index.html) **Deep Learning for Computer Vision and Natural Language Processing** *Columbia University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This graduate level research class focuses on deep learning techniques for vision and natural language processing problems. It gives an overview of the various deep learning models and techniques, and surveys recent advances in the related fields. This course uses Theano as the main programming tool. GPU programming experiences are preferred although not required. Frequent paper presentations and a heavy programming workload are expected.
- [Readings](http://llcao.net/cu-deeplearning15/reading.html)
- [Assignments](http://llcao.net/cu-deeplearning15/programming_problem.html)
- [Lecture Notes](http://llcao.net/cu-deeplearning15/index.html)
- [EE103](http://stanford.edu/class/ee103/) **Introduction to Matrix Methods** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course covers the basics of matrices and vectors, solving linear equations, least-squares methods, and many applications. It'll cover the mathematics, but the focus will be on using matrix methods in applications such as tomography, image processing, data fitting, time series prediction, finance, and many others. EE103 is based on a book that [Stephen Boyd](http://stanford.edu/~boyd/) and [Lieven Vandenberghe](http://www.seas.ucla.edu/~vandenbe/) are currently writing. Students will use a new language called [Julia](http://julialang.org/) to do computations with matrices and vectors.
- [Lectures](http://stanford.edu/class/ee103/lectures.html)
- [Book](http://stanford.edu/class/ee103/mma.html)
- [Assignments](http://stanford.edu/class/ee103/homework.html)
- [Code](http://stanford.edu/class/ee103/julia_files)
- [Info 290](http://www.ischool.berkeley.edu/courses/i290-abdt) **Analyzing Big Data with Twitter** *UC Berkeley school of information* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- In this course, UC Berkeley professors and Twitter engineers provide lectures on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter's data. Topics include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing.
- [Lecture Videos](http://www.ischool.berkeley.edu/newsandevents/audiovideo/webcast/21963)
- [Previous Years coursepage](http://blogs.ischool.berkeley.edu/i290-abdt-s12/)
- [Machine Learning: 2014-2015](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) *University of Oxford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- The course focusses on neural networks and uses the [Torch](https://github.com/torch/torch7/wiki/Cheatsheet) deep learning library (implemented in Lua) for exercises and assignments. Topics include: logistic regression, back-propagation, convolutional neural networks, max-margin learning, siamese networks, recurrent neural networks, LSTMs, hand-writing with recurrent neural networks, variational autoencoders and image generation and reinforcement learning
- [Lectures and Assignments](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
- [Source code](https://github.com/oxford-cs-ml-2015/)
- [StatLearning](https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about) **Intro to Statistical Learning** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines.
- The lectures cover all the material in [An Introduction to Statistical Learning, with Applications in R](http://www-bcf.usc.edu/~gareth/ISL/) which is a more approachable version of the [Elements of Statistical Learning](http://statweb.stanford.edu/~tibs/ElemStatLearn/) (or ESL) book.
- [10-601](http://www.cs.cmu.edu/~ninamf/courses/601sp15/) **Machine Learning** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- This course covers the theory and practical algorithms for machine learning from a variety of perspectives. It covers topics such as Bayesian networks, decision tree learning, Support Vector Machines, statistical learning methods, unsupervised learning and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC learning framework, Bayesian learning methods, margin-based learning, and Occam's Razor. Short programming assignments include hands-on experiments with various learning algorithms. This course is designed to give a graduate-level student a thorough grounding in the methodologies, technologies, mathematics and algorithms currently needed by people who do research in machine learning.
- Taught by one of the leading experts on Machine Learning - **Tom Mitchell**
- [Lectures](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml)
- [Project Ideas and Datasets](http://www.cs.cmu.edu/~tom/10701_sp11/proj.shtml)
- [10-708](http://www.cs.cmu.edu/~epxing/Class/10708-14/index.html) **Probabilistic Graphical Models** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Many of the problems in artificial intelligence, statistics, computer systems, computer vision, natural language processing, and computational biology, among many other fields, can be viewed as the search for a coherent global conclusion from local information. The probabilistic graphical models framework provides a unified view for this wide range of problems, enabling efficient inference, decision-making and learning in problems with a very large number of attributes and huge datasets. This graduate-level course will provide you with a strong foundation for both applying graphical models to complex problems and for addressing core research topics in graphical models.
- [Lecture Videos](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [Assignments](http://www.cs.cmu.edu/~epxing/Class/10708-14/homework.html)
- [Lecture notes](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [Readings](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html)
- [11-785](http://deeplearning.cs.cmu.edu/) **Deep Learning** *Carnegie Mellon University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course presents the subject through a series of seminars and labs, which will explore it from its early beginnings, and work themselves to some of the state of the art. The seminars will cover the basics of deep learning and the underlying theory, as well as the breadth of application areas to which it has been applied, as well as the latest issues on learning from very large amounts of data. We will concentrate largely, although not entirely, on the connectionist architectures that are most commonly associated with it. *Lectures* and *Reading Notes* are available on the page.
-------
### Security
- [6.857](http://courses.csail.mit.edu/6.857/2015/) **Computer and Network Security** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Emphasis on applied cryptography and may include: basic notion of systems security, cryptographic hash functions, symmetric cryptography (one-time pad, stream ciphers, block ciphers), cryptanalysis, secret-sharing, authentication codes, public-key cryptography (encryption, digital signatures), public-key attacks, web browser security, biometrics, electronic cash, viruses, electronic voting, Assignments include a group final project. Topics may vary year to year.
[Lecture Notes](http://courses.csail.mit.edu/6.857/2015/handouts)
[References](http://courses.csail.mit.edu/6.857/2015/references)
- [6.858](http://css.csail.mit.edu/6.858/2014/) **Computer Systems Security** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="" width="20" height="20" alt="Readings" title="Readings" />
- Design and implementation of secure computer systems. Lectures cover threat models, attacks that compromise security, and techniques for achieving security, based on recent research papers. Topics include operating system (OS) security, capabilities, information flow control, language security, network protocols, hardware security, and security in web applications.
- Taught by [James Mickens](http://research.microsoft.com/en-us/people/mickens/) and [Nickolai Zeldovich](http://people.csail.mit.edu/nickolai/)
- [Video Lectures and Labs](http://css.csail.mit.edu/6.858/2014/schedule.html)
- [Quizzes](http://css.csail.mit.edu/6.858/2014/quiz.html)
- [Readings](http://css.csail.mit.edu/6.858/2014/reference.html)
- [Final Projects](http://css.csail.mit.edu/6.858/2014/projects.html)
- [CIS 4930 / CIS 5930](http://www.cs.fsu.edu/~redwood/OffensiveComputerSecurity/) **Offensive Computer Security** *Florida State University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Course taught by [W. Owen Redwood](http://ww2.cs.fsu.edu/~redwood/) and [Xiuwen Liu](http://www.cs.fsu.edu/~liux/). It covers a wide range of computer security topics, starting from Secure C Coding and Reverse Engineering to Penetration Testing, Exploitation and Web Application Hacking, both from the defensive and the offensive point of view.
- [Lectures and Videos](http://www.cs.fsu.edu/~redwood/OffensiveComputerSecurity/lectures.html)
- [Assignments](http://www.cs.fsu.edu/~redwood/OffensiveComputerSecurity/assignments.html)
- [CS 155](https://courseware.stanford.edu/pg/courses/349991/cs155-spring-2013) **Computer and Network Security** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Principles of computer systems security. Attack techniques and how to defend against them. Topics include: network attacks and defenses, operating system holes, application security (web, email, databases), viruses, social engineering attacks, privacy, and digital rights management. Course projects focus on building reliable code. Recommended: Basic Unix. Primarily intended for seniors and first-year graduate students.
- [CS 161](http://www-inst.eecs.berkeley.edu/~cs161/sp15/) **Computer Security** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Introduction to computer security. Cryptography, including encryption, authentication, hash functions, cryptographic protocols, and applications. Operating system security, access control. Network security, firewalls, viruses, and worms. Software security, defensive programming, and language-based security. Case studies from real-world systems.
- [CS 259](https://courseware.stanford.edu/pg/courses/331628/cs259-winter-2013) **Security Modeling and Analysis** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course will cover a variety of contemporary network protocols and other systems with security properties. The course goal is to give students hands-on experience in using automated tools and related techniques to analyze and evaluate security mechanisms. To understand security properties and requirements, we will look at several network protocols and their properties, including secrecy, authentication, key establishment, and fairness. In parallel, the course will look at several models and tools used in security analysis and examine their advantages and limitations. In addition to fully automated finite-state model checking techniques, we will also study other approaches, such as constraint solving, process algebras, protocol logics, probabilistic model checking, game theory, and executable models based on logic programming.
- [CS 261](http://www.icir.org/vern/cs261n-Sp14/) **Internet/Network Security** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This class aims to provide a thorough grounding in network security suitable for those interested in conducting research in the area, as well as students more generally interested in either security or networking. We will also look at broader issues relating to Internet security for which networking plays a role. Topics include: denial-of-service; capabilities; network intrusion detection; worms; forensics; scanning; traffic analysis / inferring activity; architecture; protocol issues; legality and ethics; web attacks; anonymity; honeypots; botnets; spam; the underground economy; research pitfalls. The course is taught with an emphasis on seminal papers rather than bleeding-edge for a given topic.
- [CS 5430](http://www.cs.cornell.edu/courses/CS5430/2013sp/) **System Security** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="" width="20" height="20" alt="Readings" title="Readings" />
- This course discusses security for computers and networked information systems. We focus on abstractions, principles, and defenses for implementing military as well as commercial-grade secure systems.
- [Syllabus](http://www.cs.cornell.edu/courses/CS5430/2013sp/01.intro.html)
- [Lectures](http://www.cs.cornell.edu/courses/CS5430/2013sp/02.outline.html)
- [Assignments](http://www.cs.cornell.edu/courses/CS5430/2013sp/)
- [CS 161](http://www-inst.eecs.berkeley.edu/~cs161/sp15/) **Computer Security** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Introduction to computer security. Cryptography, including encryption, authentication, hash functions, cryptographic protocols, and applications. Operating system security, access control. Network security, firewalls, viruses, and worms. Software security, defensive programming, and language-based security. Case studies from real-world systems.
- [CS 261](http://www.icir.org/vern/cs261n-Sp14/) **Internet/Network Security** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This class aims to provide a thorough grounding in network security suitable for those interested in conducting research in the area, as well as students more generally interested in either security or networking. We will also look at broader issues relating to Internet security for which networking plays a role. Topics include: denial-of-service; capabilities; network intrusion detection; worms; forensics; scanning; traffic analysis / inferring activity; architecture; protocol issues; legality and ethics; web attacks; anonymity; honeypots; botnets; spam; the underground economy; research pitfalls. The course is taught with an emphasis on seminal papers rather than bleeding-edge for a given topic.
- [CS 155](https://courseware.stanford.edu/pg/courses/349991/cs155-spring-2013) **Computer and Network Security** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Principles of computer systems security. Attack techniques and how to defend against them. Topics include: network attacks and defenses, operating system holes, application security (web, email, databases), viruses, social engineering attacks, privacy, and digital rights management. Course projects focus on building reliable code. Recommended: Basic Unix. Primarily intended for seniors and first-year graduate students.
- [18-636](https://courseware.stanford.edu/pg/courses/334553/18636-spring-2013) **Browser Security** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The Web continues to grow in popularity as platform for retail transactions, financial services, and rapidly evolving forms of communication. It is becoming an increasingly attractive target for attackers who wish to compromise users' systems or steal data from other sites. Browser vendors must stay ahead of these attacks by providing features that support secure web applications. This course will study vulnerabilities in existing web browsers and the applications they render, as well as new technologies that enable web applications that were never before possible. The material will be largely based on current research problems, and students will be expected to criticize and improve existing defenses. Topics of study include (but are not limited to) browser encryption, JavaScript security, plug-in security, sandboxing, web mashups, and authentication.
- [CS 259](https://courseware.stanford.edu/pg/courses/331628/cs259-winter-2013) **Security Modeling and Analysis** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course will cover a variety of contemporary network protocols and other systems with security properties. The course goal is to give students hands-on experience in using automated tools and related techniques to analyze and evaluate security mechanisms. To understand security properties and requirements, we will look at several network protocols and their properties, including secrecy, authentication, key establishment, and fairness. In parallel, the course will look at several models and tools used in security analysis and examine their advantages and limitations. In addition to fully automated finite-state model checking techniques, we will also study other approaches, such as constraint solving, process algebras, protocol logics, probabilistic model checking, game theory, and executable models based on logic programming.
- [CSCI 4976](https://github.com/RPISEC/MBE) **Modern Binary Exploitation** *Rensselaer Polytechnic Institute* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- [CSCI 4968](https://github.com/RPISEC/MBE) **Modern Binary Exploitation** *Rensselaer Polytechnic Institute* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- This repository contains the materials as developed and used by [RPISEC](http://rpis.ec) to
teach Modern Binary Exploitation at [Rensselaer Polytechnic Institute](http://rpi.edu) in
Spring 2015. This was a university course developed and run solely by students to teach
@ -719,24 +703,37 @@ skills in vulnerability research, reverse engineering, and binary exploitation.
- This repository contains the materials as developed and used by [RPISEC](http://rpis.ec) to
teach Malware Analysis at [Rensselaer Polytechnic Institute](http://rpi.edu) in
Fall 2015. This was a university course developed and run soley by students, primarily using the
- [EECS 588](https://www.eecs.umich.edu/courses/eecs588/) **Computer & Network Security** *University of Michigan* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Taught by [J. Alex Halderman](https://jhalderm.com/) who has analyzed the security of Electronic Voting Machines in the [US](https://jhalderm.com/pub/papers/dcvoting-fc12.pdf) and [over](https://jhalderm.com/pub/papers/ivoting-ccs14.pdf) [seas](https://jhalderm.com/pub/papers/evm-ccs10.pdf).
- This intensive research seminar covers foundational work and current topics in computer systems security.
- [Readings](https://www.eecs.umich.edu/courses/eecs588/readings.html)
[Practical Malware Analysis](http://www.amazon.com/Practical-Malware-Analysis-Dissecting-Malicious/dp/1593272901)
book by Michael Sikorski and Andrew Honig, to teach skills in reverse engineering, malicious behaviour, malware,
and anti-analysis techniques.
- [Lectures Notes](https://github.com/RPISEC/Malware/tree/master/Lectures)
- [Labs](https://github.com/RPISEC/Malware/tree/master/Labs)
- [Projects](https://github.com/RPISEC/Malware/tree/master/Projects)
- [EECS 588](https://www.eecs.umich.edu/courses/eecs588/) **Computer & Network Security** *University of Michigan* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Taught by [J. Alex Halderman](https://jhalderm.com/) who has analyzed the security of Electronic Voting Machines in the [US](https://jhalderm.com/pub/papers/dcvoting-fc12.pdf) and [over](https://jhalderm.com/pub/papers/ivoting-ccs14.pdf) [seas](https://jhalderm.com/pub/papers/evm-ccs10.pdf).
- This intensive research seminar covers foundational work and current topics in computer systems security.
- [Readings](https://www.eecs.umich.edu/courses/eecs588/readings.html)
- [6.857](http://courses.csail.mit.edu/6.857/2015/) **Computer and Network Security** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Emphasis on applied cryptography and may include: basic notion of systems security, cryptographic hash functions, symmetric cryptography (one-time pad, stream ciphers, block ciphers), cryptanalysis, secret-sharing, authentication codes, public-key cryptography (encryption, digital signatures), public-key attacks, web browser security, biometrics, electronic cash, viruses, electronic voting, Assignments include a group final project. Topics may vary year to year.
[Lecture Notes](http://courses.csail.mit.edu/6.857/2015/handouts)
[References](http://courses.csail.mit.edu/6.857/2015/references)
- [6.858](http://css.csail.mit.edu/6.858/2014/) **Computer Systems Security** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="" width="20" height="20" alt="Readings" title="Readings" />
- Design and implementation of secure computer systems. Lectures cover threat models, attacks that compromise security, and techniques for achieving security, based on recent research papers. Topics include operating system (OS) security, capabilities, information flow control, language security, network protocols, hardware security, and security in web applications.
- Taught by [James Mickens](http://research.microsoft.com/en-us/people/mickens/) and [Nickolai Zeldovich](http://people.csail.mit.edu/nickolai/)
- [Video Lectures and Labs](http://css.csail.mit.edu/6.858/2014/schedule.html)
- [Quizzes](http://css.csail.mit.edu/6.858/2014/quiz.html)
- [Readings](http://css.csail.mit.edu/6.858/2014/reference.html)
- [Final Projects](http://css.csail.mit.edu/6.858/2014/projects.html)
- [18-636](https://courseware.stanford.edu/pg/courses/334553/18636-spring-2013) **Browser Security** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The Web continues to grow in popularity as platform for retail transactions, financial services, and rapidly evolving forms of communication. It is becoming an increasingly attractive target for attackers who wish to compromise users' systems or steal data from other sites. Browser vendors must stay ahead of these attacks by providing features that support secure web applications. This course will study vulnerabilities in existing web browsers and the applications they render, as well as new technologies that enable web applications that were never before possible. The material will be largely based on current research problems, and students will be expected to criticize and improve existing defenses. Topics of study include (but are not limited to) browser encryption, JavaScript security, plug-in security, sandboxing, web mashups, and authentication.
-------
###Artificial Intelligence
- [6.868J](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/index.htm) **The Society of Mind** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course is an introduction, by Prof. [Marvin Minsky](http://www.nytimes.com/2016/01/26/business/marvin-minsky-pioneer-in-artificial-intelligence-dies-at-88.html?_r=0), to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality. It incorporates ideas from psychology, artificial intelligence, and computer science to resolve theoretical issues such as wholes vs. parts, structural vs. functional descriptions, declarative vs. procedural representations, symbolic vs. connectionist models, and logical vs. common-sense theories of learning.
- [Lectures](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/video-lectures/)
- [Assignments](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/assignments/)
- [Readings](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/readings/)
- [CS L333](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm) **Introduction to Artificial Intelligence** *IIT Delhi* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Introduction to Artificial Intelligence- Problem Solving, Game Playing, Knowledge Representation, Handling uncertainty using probabilistic models and Fuzzy Logic. Expert systems and Intelligent agents. Machine Learning, Soft computing and NLP.
- [Lectures](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm)
- [Assignments](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm)
- [Readings](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm#book)
- [CS 188](http://ai.berkeley.edu/home.html) **Introduction to Artificial Intelligence** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20 " height="20" alt="Lecture Notes" title="Lecture Notes" />
- This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm. By the end of this course, you will have built autonomous agents that efficiently make decisions in fully informed, partially observable and adversarial settings. Your agents will draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue.
- [Lectures](http://ai.berkeley.edu/lecture_videos.html)
@ -751,11 +748,11 @@ and anti-analysis techniques.
- [Syllabus](http://www.cs.cornell.edu/courses/CS6700/2013sp/lectures/CS6700-Overview_v2.pptx)
- [Lectures](http://www.cs.cornell.edu/courses/CS6700/2013sp/)
- [Readings](http://www.cs.cornell.edu/courses/CS6700/2013sp/)
- [CS L333](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm) **Introduction to Artificial Intelligence** *IIT Delhi* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Introduction to Artificial Intelligence- Problem Solving, Game Playing, Knowledge Representation, Handling uncertainty using probabilistic models and Fuzzy Logic. Expert systems and Intelligent agents. Machine Learning, Soft computing and NLP.
- [Lectures](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm)
- [Assignments](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm)
- [Readings](http://www.cse.iitd.ernet.in/~saroj/AI/ai2013/ai_main_13.htm#book)
- [6.868J](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/index.htm) **The Society of Mind** *MIT* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course is an introduction, by Prof. [Marvin Minsky](http://www.nytimes.com/2016/01/26/business/marvin-minsky-pioneer-in-artificial-intelligence-dies-at-88.html?_r=0), to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality. It incorporates ideas from psychology, artificial intelligence, and computer science to resolve theoretical issues such as wholes vs. parts, structural vs. functional descriptions, declarative vs. procedural representations, symbolic vs. connectionist models, and logical vs. common-sense theories of learning.
- [Lectures](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/video-lectures/)
- [Assignments](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/assignments/)
- [Readings](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/readings/)
-------
### Computer Graphics
@ -778,9 +775,6 @@ and anti-analysis techniques.
- The study of creating, manipulating, and using visual images in the computer.
- [Assignments](http://www.cs.cornell.edu/Courses/CS4620/2014fa/index.shtml#asgn)
- [Exams](http://www.cs.cornell.edu/Courses/CS4620/2014fa/index.shtml#exams)
- [CSCI-GA.2270-001](https://mrl.nyu.edu/~perlin/courses/fall2015/) **Graduate Computer Graphics** *New York University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" />
- Step-by-step study computer graphics, with reading and homework at each lecture (Fall2015)
- [Lectures](https://mrl.nyu.edu/~perlin/courses/fall2015/)
- [CS 4670](http://www.cs.cornell.edu/courses/CS4670/2015sp/) **Introduction to Computer Vision** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments"/> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course will provide an introduction to computer vision, with topics including image formation, feature detection, motion estimation, image mosaics, 3D shape reconstruction, and object and face detection and recognition. Applications of these techniques include building 3D maps, creating virtual characters, organizing photo and video databases, human computer interaction, video surveillance, automatic vehicle navigation, and mobile computer vision. This is a project-based course, in which you will implement several computer vision algorithms throughout the semester.
- [Assignments](http://www.cs.cornell.edu/courses/CS4670/2015sp/projects/projects.html)
@ -790,6 +784,9 @@ and anti-analysis techniques.
- [Syllabus](https://canvas.instructure.com/courses/904706/assignments/syllabus)
- [Lectures](https://canvas.instructure.com/courses/904706)
- [Assignments](https://canvas.instructure.com/courses/904706/assignments)
- [CSCI-GA.2270-001](https://mrl.nyu.edu/~perlin/courses/fall2015/) **Graduate Computer Graphics** *New York University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" />
- Step-by-step study computer graphics, with reading and homework at each lecture (Fall2015)
- [Lectures](https://mrl.nyu.edu/~perlin/courses/fall2015/)
-------
### Misc
@ -809,6 +806,9 @@ and anti-analysis techniques.
- [Assignments](https://github.com/mikeizbicki/ucr-cs100/tree/2015winter/assignments)
- [CS 108](http://web.stanford.edu/class/cs108/) **Object Oriented System Design** *Stanford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Software design and construction in the context of large OOP libraries. Taught in Java. Topics: OOP design, design patterns, testing, graphical user interface (GUI) OOP libraries, software engineering strategies, approaches to programming in teams.
- [CS 168](https://inst.eecs.berkeley.edu/~cs168/fa15/) **Computer Networks** *UC Berkeley*<img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This is an undergraduate level course covering the fundamental concepts of networking as embodied in the Internet. The course will cover a wide range of topics; see the lecture schedule for more details. While the class has a textbook, we will not follow its order of presentation but will instead use the text as a reference when covering each individual topic. The course will also have several projects that involve programming (in Python).
- You should know programming, data structures, and software engineering. In terms of mathematics, your algebra should be very solid, you need to know basic probability, and you should be comfortable with thinking abstractly. The TAs will spend very little time reviewing material that is not specific to networking. We assume that you either know the material covered in those courses, or are willing to learn the material as necessary. We won't cover any of this material in lecture.
- [CS 193a](http://web.stanford.edu/class/cs193a/lectures.shtml) **Android App Development, Spring 2016** *Stanford University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Course Description: This course provides an introduction to developing applications for the Android mobile platform.
- Prerequisite: CS 106B or equivalent. Java experience highly recommended. OOP highly recommmended.
@ -825,6 +825,13 @@ and anti-analysis techniques.
- The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control.
- [Lectures](http://see.stanford.edu/see/lecturelist.aspx?coll=86cc8662-f6e4-43c3-a1be-b30d1d179743)
- [Assignments](http://see.stanford.edu/see/materials/aiircs223a/assignments.aspx)
- [CS 262a](http://www.cs.berkeley.edu/~brewer/cs262/) **Advanced Topics in Computer Systems** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- CS262a is the first semester of a year-long sequence on computer systems research, including operating systems, database systems, and Internet infrastructure systems. The goal of the course is to cover a broad array of research topics in computer systems, and to engage you in top-flight systems research. The first semester is devoted to basic thematic issues and underlying techniques in computer systems, while the second semester goes deeper into topics related to scalable, parallel and distributed systems. The class is based on a discussion of important research papers and a research project.
- **Parts**: Some Classics, Persistent Storage, Concurrency, Higher-Level Models, Virtual Machines, Cloud Computing, Parallel and Distributed Computing, Potpourri.
- Prerequisites: The historical prerequisite was to pass an entrance exam in class, which covered undergraduate operating systems material (similar to [UCB's CS162](https://cs162.eecs.berkeley.edu/)). There is no longer an exam. However, if you have not already taken a decent undergrad OS class, you should talk with me before taking this class. The exam had the benefit of "paging in" the undergrad material, which may have been its primary value (since the pass rate was high).
- [Readings & Lectures](http://www.cs.berkeley.edu/~brewer/cs262/)
- [CS 294](http://inst.eecs.berkeley.edu/~cs294-101/sp15/) **Cutting-edge Web Technologies** *Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Want to learn what makes future web technologies tick? Join us for the class where we will dive into the internals of many of the newest web technologies, analyze and dissect them. We will conduct survey lectures to provide the background and overview of the area as well as invite guest lecturers from various leading projects to present their technologies.
- [CS 411](http://video.bilkent.edu.tr/course_videos.php?courseid=10) **Software Architecture Design** *Bilkent University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- This course teaches the basic concepts, methods and techniques for designing software architectures. The topics include: rationale for software architecture design, modeling software architecture design, architectural styles/patterns, architectural requirements analysis, comparison and evaluation of architecture design methods, synthesis-based software architecture design, software product-line architectures, domain modeling, domain engineering and application engineering, software architecture implementation, evaluating software architecture designs.
- [CS 3152](http://www.cs.cornell.edu/courses/CS3152/2014sp/) **Introduction to Computer Game Development** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments"/> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
@ -923,8 +930,6 @@ and anti-analysis techniques.
- [Lectures](http://www.schneems.com/ut-rails/)
- [Assignments](http://www.schneems.com/ut-rails/)
- [Videos](https://www.youtube.com/playlist?list=PL7A85FD7803A8CB1F)
- [CS294](http://inst.eecs.berkeley.edu/~cs294-101/sp15/) **Cutting-edge Web Technologies** *Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- Want to learn what makes future web technologies tick? Join us for the class where we will dive into the internals of many of the newest web technologies, analyze and dissect them. We will conduct survey lectures to provide the background and overview of the area as well as invite guest lecturers from various leading projects to present their technologies.
- [SCICOMP](http://mlecture.uni-bremen.de/ml/index.php?option=com_content&view=article&id=233) **An Introduction to Efficient Scientific Computation** *Universität Bremen* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" />
- This is a graduate course in scientific computing created and taught by [Oliver Serang](http://colorfulengineering.org/) in 2014, which covers topics in computer science and statistics with applications from biology. The course is designed top-down, starting with a problem and then deriving a variety of solutions from scratch.
- Topics include memoization, recurrence closed forms, string matching (sorting, hash tables, radix tries, and suffix tries), dynamic programming (e.g. Smith-Waterman and Needleman-Wunsch), Bayesian statistics (e.g. the envelope paradox), graphical models (HMMs, Viterbi, junction tree, belief propagation), FFT, and the probabilistic convolution tree.
@ -933,11 +938,3 @@ and anti-analysis techniques.
- This is an introductory course on Networking for graduate students. It follows a top-down approach to teaching Computer Networks, so it starts with the Application layer which most of the students are familiar with and as the course unravels we learn more about transport, network and link layers of the protocol stack.
- As far as prerequisites are concerned - basic computer, programming and probability theory background is required.
- The course site contains links to the lecture videos, reading material and assignments.
- [CS 168](https://inst.eecs.berkeley.edu/~cs168/fa15/) **Computer Networks** *UC Berkeley*<img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- This is an undergraduate level course covering the fundamental concepts of networking as embodied in the Internet. The course will cover a wide range of topics; see the lecture schedule for more details. While the class has a textbook, we will not follow its order of presentation but will instead use the text as a reference when covering each individual topic. The course will also have several projects that involve programming (in Python).
- You should know programming, data structures, and software engineering. In terms of mathematics, your algebra should be very solid, you need to know basic probability, and you should be comfortable with thinking abstractly. The TAs will spend very little time reviewing material that is not specific to networking. We assume that you either know the material covered in those courses, or are willing to learn the material as necessary. We won't cover any of this material in lecture.
- [CS 262a](http://www.cs.berkeley.edu/~brewer/cs262/) **Advanced Topics in Computer Systems** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- CS262a is the first semester of a year-long sequence on computer systems research, including operating systems, database systems, and Internet infrastructure systems. The goal of the course is to cover a broad array of research topics in computer systems, and to engage you in top-flight systems research. The first semester is devoted to basic thematic issues and underlying techniques in computer systems, while the second semester goes deeper into topics related to scalable, parallel and distributed systems. The class is based on a discussion of important research papers and a research project.
- **Parts**: Some Classics, Persistent Storage, Concurrency, Higher-Level Models, Virtual Machines, Cloud Computing, Parallel and Distributed Computing, Potpourri.
- Prerequisites: The historical prerequisite was to pass an entrance exam in class, which covered undergraduate operating systems material (similar to [UCB's CS162](https://cs162.eecs.berkeley.edu/)). There is no longer an exam. However, if you have not already taken a decent undergrad OS class, you should talk with me before taking this class. The exam had the benefit of "paging in" the undergrad material, which may have been its primary value (since the pass rate was high).
- [Readings & Lectures](http://www.cs.berkeley.edu/~brewer/cs262/)