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Awesome Courses
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===============
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# Awesome Courses [](https://github.com/sindresorhus/awesome)
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Introduction
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------------
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@ -15,6 +15,7 @@ Table of Contents
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- [CS Theory](#cs-theory)
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- [Introduction to CS](#introduction-to-cs)
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- [Machine Learning](#machine-learning)
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- [Security](#security)
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- [Misc](#misc)
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### Legend
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@ -35,7 +36,7 @@ Courses
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- [Lecture Notes](http://www-inst.eecs.berkeley.edu/~cs61c/sp15/#Calendar)
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- [Resources](http://www-inst.eecs.berkeley.edu/~cs61c/sp15/#Resources)
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- [Old Exams](https://hkn.eecs.berkeley.edu/exams/course/CS/61C)
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- [CS 107](http://web.stanford.edu/class/cs107/index.html) **Computer Organization & Systems** *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" />
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- [CS 107](https://courseware.stanford.edu/pg/courses/lectures/371747) **Computer Organization & Systems** *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" />
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<img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
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- CS107 is the third course in Stanford's introductory programming sequence. The course will work from the C programming language down to the microprocessor to de-mystify the machine. With a complete understanding of how computer systems execute programs and manipulate data, you will become a more effective programmer, especially in dealing with issues of debugging, performance, portability, and robustness.
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- [Lecture Videos](https://www.youtube.com/playlist?list=PL08D9FA018A965057&spfreload=10)
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@ -47,6 +48,10 @@ Courses
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- [CS 162](http://cs162.eecs.berkeley.edu/) **Operating Systems and Systems Programming** *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/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" />
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- Operating Systems course by the Chair of EECS, UC Berkeley [David Culler](http://www.cs.berkeley.edu/~culler/)
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- [Youtube Playlist](https://www.youtube.com/playlist?list=PL-XXv-cvA_iAARFmCufZ6XeMPPgAzNSNa) Fall 2014 lectures
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- [CS 168](https://inst.eecs.berkeley.edu/~cs168/fa14/) **Introduction to the Internet: Architecture and Protocols** *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/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
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- 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).
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- [Lecture Notes & Assignments](https://inst.eecs.berkeley.edu/~cs168/fa14/class.html)
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- [Discussion Notes](https://inst.eecs.berkeley.edu/~cs168/fa14/)
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- [CS 186](https://sites.google.com/site/cs186fall2013/home) **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" />
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- 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.
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- [Lecture Notes](https://sites.google.com/site/cs186fall2013/section-notes)
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@ -227,7 +232,13 @@ Courses
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- [Lecture Videos](http://cs.wheaton.edu/~tvandrun/dmfp/)
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- [Assignments](http://cs.wheaton.edu/~tvandrun/dmfp/source.html)
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- [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" />
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- 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.
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- 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.
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- [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" />
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- 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.
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- 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.
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- It covers concepts such as atomicity, safety, liveness and deadlock.
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- It covers how to measure and understand performance and scalability of parallel programs.
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- It covers tools and methods to find bugs in concurrent programs.
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-------
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@ -269,6 +280,9 @@ Courses
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- [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" />
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- 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.
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- [Lecture Videos](http://www.cs.sunysb.edu/~algorith/video-lectures/)
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- [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" />
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- 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.
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- [Lectures, Assignments, and Exams](http://courses.cs.washington.edu/courses/cse331/15sp/#all)
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- [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" />
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- Fantastic repository of theory and practice problems across various topics for students who are interested to participate in ACM-ICPC.
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- [Lectures and Assignments](http://stanford.edu/~liszt90/acm/notebook.html)
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@ -375,31 +389,32 @@ Courses
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- [CS 50](https://cs50.harvard.edu/) **Introduction to Computer Science** *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" />
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- CS50x is Harvard College's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan.
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- [Lectures](https://cs50.harvard.edu/lectures)
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- [CS 61A](http://cs61a.org/) **Structure and Interpretation of Computer Programs [Python]** *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" />
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- [Problem Sets](https://cs50.harvard.edu/psets)
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- [CS 61A](http://cs61a.org/) **Structure and Interpretation of Computer Programs [Python]** *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" />
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- In CS 61A, we are interested in teaching you about programming, not about how to use one particular programming language. We consider a series of techniques for controlling program complexity, such as functional programming, data abstraction, and object-oriented programming. Mastery of a particular programming language is a very useful side effect of studying these general techniques. However, our hope is that once you have learned the essence of programming, you will find that picking up a new programming language is but a few days' work.
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- [Lecture Resources by Type](http://cs61a.org/by_type.html)
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- [Lecture Resources by Topic](http://cs61a.org/by_topic.html)
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- [Additional Resources](http://cs61a.org/resources.html)
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- [Practice Problems](http://cs61a.org/problems/)
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- [Extra Lectures](http://cs61a.org/extra.html)
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- [CS 61AS](http://berkeley-cs61as.github.io/) **Structure & Interpretation of Computer Programs [Racket]** *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" />
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- A self-paced version of the CS61 Course but in Racket / Scheme. 61AS is a great introductory course that will ease you into all the amazing concepts that future CS courses will cover, so remember to keep an open mind, have fun, and always respect the data abstraction
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- [CS 61AS](http://berkeley-cs61as.github.io/) **Structure & Interpretation of Computer Programs [Racket]** *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" />
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- A self-paced version of the CS61 Course but in Racket / Scheme. 61AS is a great introductory course that will ease you into all the amazing concepts that future CS courses will cover, so remember to keep an open mind, have fun, and always respect the data abstraction
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- [Lecture Videos](https://www.youtube.com/course?category=University%2FEngineering%2FComputer%2520Science%2FProgramming%2520Languages&list=EC6D76F0C99A731667)
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- [Assignments and Notes](http://berkeley-cs61as.github.io/textbook.html)
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- [CS 101](http://online.stanford.edu/course/computer-science-101-self-paced) **Computer Science 101** *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" />
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- CS101 teaches the essential ideas of Computer Science for a zero-prior-experience audience. Participants play and experiment with short bits of "computer code" to bring to life to the power and limitations of computers.
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- Lectures videos will available for free after registration.
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- [CS 106A](http://see.stanford.edu/see/courseinfo.aspx?coll=824a47e1-135f-4508-a5aa-866adcae1111) **Programming Methodology** *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" />
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- [CS 106A](https://see.stanford.edu/Course/CS106A) **Programming Methodology** *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" />
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- This course is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Programming Methodology teaches the widely-used Java programming language along with good software engineering principles.
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- [Lecture Videos](http://see.stanford.edu/see/lecturelist.aspx?coll=824a47e1-135f-4508-a5aa-866adcae1111)
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- [Assignments](http://see.stanford.edu/see/materials/icspmcs106a/assignments.aspx)
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- [All materials in a zip file](http://see.stanford.edu/materials/icspmcs106a/ProgrammingMethodologyAllMaterials.zip)
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- [CS 106B](http://see.stanford.edu/see/courseinfo.aspx?coll=11f4f422-5670-4b4c-889c-008262e09e4e) **Programming Abstractions** *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" />
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- [CS 106B](https://see.stanford.edu/Course/CS106B) **Programming Abstractions** *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" />
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- This course is the natural successor to Programming Methodology and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming language, which is similar to both C and Java.
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- [Lectures](http://see.stanford.edu/see/lecturelist.aspx?coll=11f4f422-5670-4b4c-889c-008262e09e4e)
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- [Assignments](http://see.stanford.edu/see/materials/icspacs106b/assignments.aspx)
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- [All materials in a zip file](http://see.stanford.edu/materials/icspacs106b/ProgrammingAbstractionsAllMaterials.zip)
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- [CS 107](http://see.stanford.edu/see/courseinfo.aspx?coll=2d712634-2bf1-4b55-9a3a-ca9d470755ee) **Programming Paradigms** *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" />
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- [CS 107](https://see.stanford.edu/Course/CS107) **Programming Paradigms** *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" />
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- Topics: Advanced memory management features of C and C++; the differences between imperative and object-oriented paradigms. The functional paradigm (using LISP) and concurrent programming (using C and C++)
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- [Lectures](http://see.stanford.edu/see/lecturelist.aspx?coll=2d712634-2bf1-4b55-9a3a-ca9d470755ee)
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- [Assignments](http://see.stanford.edu/see/materials/icsppcs107/assignments.aspx)
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@ -470,15 +485,22 @@ Courses
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- [Lectures and Assignments 2](http://www.eng.utah.edu/~cs2420-20/schedule.html)
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- [Textbook](http://htdp.org/2003-09-26/Book/curriculum.html)
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- [Racket Language](http://racket-lang.org/)
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- [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" />
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- 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.
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- [Lectures and Other resources](https://www.cs.hmc.edu/twiki/bin/view/ModularCS1)
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-------
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### Machine Learning
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- [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" />
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- 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.
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- 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.
|
||||
- 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)
|
||||
@ -494,6 +516,11 @@ Courses
|
||||
- [Slides](http://cs109.github.io/2014/pages/schedule.html)
|
||||
- [Labs and Assignments](http://cs109.github.io/2014/pages/homework.html)
|
||||
- [2013 Lectures](http://cm.dce.harvard.edu/2014/01/14328/publicationListing.shtml) *(slightly better)*
|
||||
- [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)
|
||||
- [Projects](http://ai.berkeley.edu/project_overview.html)
|
||||
- [Exams](http://ai.berkeley.edu/exams.html)
|
||||
- [CS 224d](http://cs224d.stanford.edu/) **Deep Learning for Natural Language Processing** *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" />
|
||||
- Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc. There are a large variety of underlying tasks and machine learning models powering NLP applications. Recently, deep learning approaches have obtained very high performance across many different NLP tasks. These models can often be trained with a single end-to-end model and do not require traditional, task-specific feature engineering. In this spring quarter course students will learn to implement, train, debug, visualize and invent their own neural network models. The course provides a deep excursion into cutting-edge research in deep learning applied to NLP.
|
||||
- [Syllabus](http://cs224d.stanford.edu/syllabus.html)
|
||||
@ -502,6 +529,10 @@ Courses
|
||||
- Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. This course is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. During the 10-week course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision.
|
||||
- [Lecture Notes](http://cs231n.stanford.edu/syllabus.html)
|
||||
- [Github Page](http://cs231n.github.io/)
|
||||
- [CS 287](http://www.cs.berkeley.edu/~pabbeel/cs287-fa13/) **Advanced Robotics** *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/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
|
||||
- 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 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/)
|
||||
@ -522,6 +553,45 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
||||
- 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
|
||||
- [Lecutures 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 programminging 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)
|
||||
|
||||
-------
|
||||
|
||||
###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, crypotographic hash functions, symmetric crypotography (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 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.
|
||||
|
||||
-------
|
||||
|
||||
@ -539,10 +609,6 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
||||
- An introductory course in computer vision and computational photography focusing on four topics: image features, image morphing, shape matching, and image search.
|
||||
- [Lectures](https://alliance.seas.upenn.edu/~cis581/wiki/index.php?title=Schedule)
|
||||
- [Assignments](https://alliance.seas.upenn.edu/~cis581/wiki/index.php?title=Projects)
|
||||
- [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 75](http://ocw.tufts.edu/Course/75) **Introduction to Game Development** *Tufts 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" />
|
||||
- The course taught by [Ming Y. Chow](http://mchow01.github.io) teaches game development initially in PyGame through Python, before moving on to addressing all facets of game development. Topics addressed include game physics, sprites, animation, game development methodology, sound, testing, MMORPGs and online games, and addressing mobile development in Android, HTML5, and iOS. Most to all of the development is focused on PyGame for learning principles
|
||||
- [Text Lectures](http://ocw.tufts.edu/Course/75/Learningunits)
|
||||
@ -625,11 +691,6 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
||||
- Applications from science and engineering
|
||||
- [Lectures](http://www.cs.cornell.edu/~bindel/class/cs5220-f11/lectures.html)
|
||||
- [Assignments](http://www.cs.cornell.edu/~bindel/class/cs5220-f11/assignments.html)
|
||||
- [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="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" 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 5540](https://sites.google.com/site/cs5540sp2013/) **Computational Techniques for Analyzing Clinical Data** *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" />
|
||||
- CS5540 is a masters-level course that covers a wide range of clinical problems and their associated computational challenges. The practice of medicine is filled with digitally accessible information about patients, ranging from EKG readings to MRI images to electronic health records. This poses a huge opportunity for computer tools that make sense out of this data. Computation tools can be used to answer seemingly straightforward questions about a single patient's test results (“Does this patient have a normal heart rhythm?”), or to address vital questions about large populations (“Is there any clinical condition that affects the risks of Alzheimer”). In CS5540 we will look at many of the most important sources of clinical data and discuss the basic computational techniques used for their analysis, ranging in sophistication from current clinical practice to state-of-the-art research projects.
|
||||
- [Syllabus](https://sites.google.com/site/cs5540sp2013/home/course-description)
|
||||
@ -706,7 +767,7 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
||||
- [Lecture Videos](http://www.ischool.berkeley.edu/newsandevents/audiovideo/webcast/21963)
|
||||
- [Previous Years coursepage](http://blogs.ischool.berkeley.edu/i290-abdt-s12/)
|
||||
- [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.
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- 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.
|
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- [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" />
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- 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.
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- Taught by [Dr. Ching-Yung Lin](http://researcher.watson.ibm.com/researcher/view.php?person=us-chingyung)
|
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@ -716,15 +777,7 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
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- 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.
|
||||
- [Lecture videos on Youtube](https://www.youtube.com/user/fillwithlight/videos) and for direct [download](http://mlecture.uni-bremen.de/ml/index.php?option=com_content&view=article&id=233)
|
||||
|
||||
- [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="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" 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)
|
||||
- [14-740](http://www.ini740.com/F14/index.html) **Fundamentals of Computer Networks** *CMU* <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" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
|
||||
- [14-740](http://www.ini740.com/F15/index.html) **Fundamentals of Computer Networks** *CMU* <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" /> <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 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.
|
||||
|
||||
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Reference in New Issue
Block a user