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@ -110,7 +110,7 @@ Courses
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- [Lecture Notes](http://comp.uark.edu/~wingning/csce3613/CourseNote3613.html)
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- [Readings](http://comp.uark.edu/~wingning/csce3613/Link3613.html)
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- [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" />
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- 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.
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- 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 recommended reading materials. What's more, there are a series of hands-on lab materials, helping you easily understand OS.
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- [Assignments](http://www.cs.nyu.edu/~mwalfish/classes/15sp/labs.html)
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- [Lectures](http://www.cs.nyu.edu/~mwalfish/classes/15sp/syllabus.html)
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- [Old Exams](http://www.cs.nyu.edu/~mwalfish/classes/15sp/exams.html)
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@ -276,7 +276,7 @@ Courses
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- [Lecture Notes](https://www.dropbox.com/sh/zanwtoflw4pcfu8/5pdT6axS3y)
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- [Projects](http://matt.might.net/teaching/compilers/spring-2015/#projects)
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- [CS 6118](http://www.cs.cornell.edu/courses/CS6118/2012fa/) **Types and Semantics** *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" />
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- 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.
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- 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 conventional 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.
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- [Syllabus](http://www.cs.cornell.edu/courses/CS6118/2012fa/)
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- [Lectures](http://www.cs.cornell.edu/courses/CS6118/2012fa/)
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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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@ -317,12 +317,12 @@ Courses
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- [CS 61B](http://datastructur.es/sp16/) **Data Structures** *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" /> <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 course, you will study advanced programming techniques including data structures, encapsulation, abstract data types, interfaces, and algorithms for sorting and searching, and you will get a taste of “software engineering”—the design and implementation of large programs.
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- [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)
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- [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 useful resources for Java Documentation, Data Structure Resources, Git/GitHub and Java Development Resources. [Resources](http://datastructur.es/sp16/resources.html)
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- [Labs](http://www.cs.berkeley.edu/~jrs/61b/lab/index.html) The link to labs and projects is included in the website.
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- [Lecture Videos](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iC2Khb1B5NnbE7SHPQ1-W17)
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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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- [Lectures and Assignments](https://github.com/jaehyunp/stanfordacm)
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- [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" />
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- 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.
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- [Lecture Videos](http://people.seas.harvard.edu/~minilek/cs224/fall14/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf))
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@ -338,11 +338,10 @@ Courses
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- This data structures course introduces C++, linked-lists, stacks, queues, trees, numerical representation, hash tables, priority queues, heaps, huffman coding, graphs, and x86 assembly.
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- [Lectures](http://aaronbloomfield.github.io/pdr/slides/)
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- [Assignments](http://aaronbloomfield.github.io/pdr/labs/)
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- [CS 4820](http://www.cs.cornell.edu/courses/CS4820/2014sp/) **Introduction to Analysis of Algorithms** *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" />
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- [CS 4820](http://www.cs.cornell.edu/courses/CS4820/2015sp/) **Introduction to Analysis of Algorithms** *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" />
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- This course develops techniques used in the design and analysis of algorithms, with an emphasis on problems arising in computing applications. Example applications are drawn from systems and networks, artificial intelligence, computer vision, data mining, and computational biology. This course covers four major algorithm design techniques (greedy algorithms, divide and conquer, dynamic programming, and network flow), computability theory focusing on undecidability, computational complexity focusing on NP-completeness, and algorithmic techniques for intractable problems, including identification of structured special cases, approximation algorithms, and local search heuristics.
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- [Lectures](http://www.cs.cornell.edu/courses/CS4820/2014sp/lectures/)
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- [Assignments](http://www.cs.cornell.edu/courses/CS4820/2014sp/homework/)
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- [Syllabus](http://www.cs.cornell.edu/courses/CS4820/2014sp/syllabus/)
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- [Lectures](http://www.cs.cornell.edu/courses/CS4820/2015sp/lectures/)
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- [Syllabus](http://www.cs.cornell.edu/courses/CS4820/2015sp/syllabus/)
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- [CSCI 104](http://www-scf.usc.edu/~csci104/20142/lectures/) **Data Structures and Object Oriented Design** <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" /> *University of Southern California (USC)*
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- [Lectures](http://www-scf.usc.edu/~csci104/20142/lectures)
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- [Labs](http://www-scf.usc.edu/~csci104/20142/labs)
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@ -380,7 +379,7 @@ Courses
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- [Handouts](http://courses.csail.mit.edu/iap/interview/materials.php)
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- [Topics Covered](http://courses.csail.mit.edu/iap/interview/calendar.php)
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- [6.006](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/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" />
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- 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.
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- 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.
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- [Lecture Videos](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/lecture-videos/)
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- [Assignments](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/assignments/)
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- [Readings](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/readings/)
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@ -457,7 +456,7 @@ Courses
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- [Syllabus](http://www.cs.cornell.edu/~dsteurer/toc13/syllabus/)
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- [Lectures](http://www.cs.cornell.edu/~dsteurer/toc13/lectures/)
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- [Assignments](http://www.cs.cornell.edu/~dsteurer/toc13/homework/)
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- [CS 6810](http://www.cs.cornell.edu/~dsteurer/complexity12/) **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" />
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- [CS 6810](https://complexity16.dsteurer.org/) **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" />
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- This graduate course gives a broad introduction to complexity theory, including classical results and recent developments. Complexity theory aims to understand the power of efficient computation (when computational resources like time and space are limited). Many compelling conceptual questions arise in this context. Most of these questions are (surprisingly?) difficult and far from being resolved. Nevertheless, a lot of progress has been made toward understanding them (and also why they are difficult). We will learn about these advances in this course. A theme will be combinatorial constructions with random-like properties, e.g., expander graphs and error-correcting codes. Some examples:
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- Is finding a solution inherently more difficult than verifying it?
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- Do more computational resources mean more computing power?
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@ -465,9 +464,9 @@ Courses
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- Are randomized algorithms more powerful than deterministic ones?
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- Is it easier to solve problems in the average case than in the worst case?
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- Are quantum computers more powerful than classical ones?
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- [Syllabus](http://www.cs.cornell.edu/~dsteurer/complexity12/)
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- [Lectures](http://www.cs.cornell.edu/~dsteurer/complexity12/#lectures)
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- [Assignments](http://www.cs.cornell.edu/~dsteurer/complexity12/#homework)
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- [Syllabus](https://complexity16.dsteurer.org/syllabus/)
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- [Lectures](https://complexity16.dsteurer.org/lectures/)
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- [Assignments](https://complexity16.dsteurer.org/homework/)
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- [CSCE 3193](http://www.csce.uark.edu/~sgauch/3193/S11/index.html) **Programming Paradigms** *University of Arkansas (Fayetteville)* <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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- Programming in different paradigms with emphasis on object oriented programming, network programming and functional programming. Survey of programming languages, event driven programming, concurrency, software validation.
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- [Syllabus](http://www.csce.uark.edu/~sgauch/3193/S11/syllabus.html)
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@ -490,9 +489,10 @@ Courses
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- [Curriculum](http://bjc.berkeley.edu)
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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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- [Problem Sets](https://cs50.harvard.edu/psets)
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- [Lectures](http://cs50.tv/2017/fall/#about,lectures)
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- [Problem Sets](http://cs50.tv/2017/fall/#about,psets)
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- The course can also be taken from [edX](https://www.edx.org/course/introduction-computer-science-harvardx-cs50x).
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- The course's OpenCourseware resides [here](http://cs50.tv)
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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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- Lectures videos will available for free after registration.
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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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- [Lecture Videos](https://see.stanford.edu/Course/CS106A)
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- [Assignments](https://see.stanford.edu/Course/CS106A)
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- [All materials in a zip file](http://see.stanford.edu/materials/icspmcs106a/ProgrammingMethodologyAllMaterials.zip)
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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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- [Lectures](https://see.stanford.edu/Course/CS106B)
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- [Assignments](https://see.stanford.edu/Course/CS106B)
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- [All materials in a zip file](http://see.stanford.edu/materials/icspacs106b/ProgrammingAbstractionsAllMaterials.zip)
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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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- [Lectures](https://see.stanford.edu/Course/CS107)
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- [Assignments](https://see.stanford.edu/Course/CS107)
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- [CS 109](http://otfried.org/courses/cs109/index.html) **Programming Practice Using Scala** *KAIST* <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 introduces basic concepts of programming and computer science, such as dynamic and static typing, dynamic memory allocation, objects and methods, binary representation of numbers, using an editor and compiler from the command line, running programs with arguments from the command line, using libraries, and the use of basic data structures such as arrays, lists, sets, and maps. We will use Scala for this course.
|
||||
- [Lectures] (http://otfried.org/courses/cs109/index.html)
|
||||
@ -648,7 +648,7 @@ Courses
|
||||
- [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)
|
||||
- [Lectures and Assignments](http://wpressutexas.net/forum/)
|
||||
- [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/)
|
||||
@ -685,6 +685,11 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
||||
- [Book](http://stanford.edu/class/ee103/mma.html)
|
||||
- [Assignments](http://stanford.edu/class/ee103/homework.html)
|
||||
- [Code](http://stanford.edu/class/ee103/julia_files)
|
||||
- [Fast.ai Introduction to Machine Learning for Coders](http://course.fast.ai/ml.html) *Fast.ai / University of San Francisco* <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" />
|
||||
- There are around 24 hours of lessons, and you should plan to spend around 8 hours a week for 12 weeks to complete the material. The course is based on lessons recorded at the University of San Francisco for the Masters of Science in Data Science program. We assume that you have at least one year of coding experience, and either remember what you learned in high school math, or are prepared to do some independent study to refresh your knowledge.
|
||||
- [Lecture Videos](http://course.fast.ai/lessonsml1/lessonsml1.html)
|
||||
- [Lecture Notes](https://medium.com/@hiromi_suenaga/machine-learning-1-lesson-1-84a1dc2b5236)
|
||||
- [Jupyter Notebooks](https://github.com/fastai/fastai/tree/master/courses/ml1)
|
||||
- [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)
|
||||
@ -735,7 +740,7 @@ Topics covered include probability theory and Bayesian inference; univariate dis
|
||||
- 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" />
|
||||
- [CS 155](https://crypto.stanford.edu/cs155/) **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.
|
||||
@ -759,7 +764,7 @@ skills in vulnerability research, reverse engineering, and binary exploitation.
|
||||
- [CSCI 4976](https://github.com/RPISEC/Malware) **Malware Analysis** *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 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
|
||||
Fall 2015. This was a university course developed and run solely 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.
|
||||
@ -821,11 +826,6 @@ and anti-analysis techniques.
|
||||
- This course provides a comprehensive introduction to computer graphics. Focuses on fundamental concepts and techniques, and their cross-cutting relationship to multiple problem domains in graphics (rendering, animation, geometry, imaging). Topics include: sampling, aliasing, interpolation, rasterization, geometric transformations, parameterization, visibility, compositing, filtering, convolution, curves & surfaces, geometric data structures, subdivision, meshing, spatial hierarchies, ray tracing, radiometry, reflectance, light fields, geometric optics, Monte Carlo rendering, importance sampling, camera models, high-performance ray tracing, differential equations, time integration, numerical differentiation, physically-based animation, optimization, numerical linear algebra, inverse kinematics, Fourier methods, data fitting, example-based synthesis.
|
||||
- [Lectures and Readings](http://15462.courses.cs.cmu.edu/fall2015/reading)
|
||||
- [Assignments and Quizes](http://15462.courses.cs.cmu.edu/fall2015/exercises)
|
||||
- [CS 123](http://cs.brown.edu/courses/csci1230/index.html) **Introduction to Computer Graphics** *Brown 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" />
|
||||
- This course offers an in-depth exploration of fundamental concepts in 2D and 3D computer graphics. It introduces 2D raster graphics techniques, including scan conversion, simple image processing, interaction techniques and user interface design. The bulk of the course is devoted to 3D modeling, geometric transformations, and 3D viewing and rendering.
|
||||
- [Lectures](http://cs.brown.edu/courses/csci1230/lectures.html)
|
||||
- [Labs](http://cs.brown.edu/courses/csci1230/labs.html)
|
||||
- [Demos](http://cs.brown.edu/courses/csci1230/demos.html)
|
||||
- [CS 378](https://github.com/ut-cs378-vision-2014fall/course-info) **3D Reconstruction with Computer Vision** *UTexas* <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" />
|
||||
- In this lab-based class, we'll dive into practical applications of 3D reconstruction, combining hardware and software to build our own 3D environments from scratch. We'll use open-source frameworks like OpenCV to do the heavy lifting, with the focus on understanding and applying state-of-the art approaches to geometric computer vision
|
||||
- [Lectures](https://github.com/ut-cs378-vision-2014fall/course-info/tree/master/meeting-notes)
|
||||
@ -842,6 +842,11 @@ 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 1230](http://cs.brown.edu/courses/csci1230/index.html) **Introduction to Computer Graphics** *Brown 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" />
|
||||
- This course offers an in-depth exploration of fundamental concepts in 2D and 3D computer graphics. It introduces 2D raster graphics techniques, including scan conversion, simple image processing, interaction techniques and user interface design. The bulk of the course is devoted to 3D modeling, geometric transformations, and 3D viewing and rendering.
|
||||
- [Lectures](http://cs.brown.edu/courses/csci1230/lectures.html)
|
||||
- [Labs](http://cs.brown.edu/courses/csci1230/labs.html)
|
||||
- [Demos](http://cs.brown.edu/courses/csci1230/demos.html)
|
||||
- [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/)
|
||||
@ -909,10 +914,10 @@ and anti-analysis techniques.
|
||||
- [Syllabus](http://www.cs.cornell.edu/courses/CS4154/2014fa/about/faq.php)
|
||||
- [Lectures](http://www.cs.cornell.edu/courses/CS4154/2014fa/lectures/index.php)
|
||||
- [Assignments](http://www.cs.cornell.edu/courses/CS4154/2014fa/assignments/index.php)
|
||||
- [CS 4812](https://courses.cit.cornell.edu/physics4481-7681_2014sp/) **Quantum Information Processing** *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" />
|
||||
- [CS 4812](https://courses.cit.cornell.edu/physics4481-7681_2018fa/) **Quantum Information Processing** *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" />
|
||||
- Hardware that exploits quantum phenomena can dramatically alter the nature of computation. Though constructing a working quantum computer is a formidable technological challenge, there has been much recent experimental progress. In addition, the theory of quantum computation is of interest in itself, offering strikingly different perspectives on the nature of computation and information, as well as providing novel insights into the conceptual puzzles posed by the quantum theory. The course is intended both for physicists, unfamiliar with computational complexity theory or cryptography, and also for computer scientists and mathematicians, unfamiliar with quantum mechanics. The prerequisites are familiarity (and comfort) with finite dimensional vector spaces over the complex numbers, some standard group theory, and ability to count in binary.
|
||||
- [Syllabus](http://www.cs.cornell.edu/~ginsparg/physics/P4481-P7681-CS4812/Fa12.html)
|
||||
- [Lectures](https://courses.cit.cornell.edu/physics4481-7681_2014sp/)
|
||||
- [Syllabus](https://courses.cit.cornell.edu/physics4481-7681_2018fa/)
|
||||
- [Lectures](https://courses.cit.cornell.edu/physics4481-7681_2018fa/)
|
||||
- [CS 4860](http://www.cs.cornell.edu/courses/CS4860/2012fa/) **Applied Logic** *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" />
|
||||
- In addition to basic first-order logic, when taught by Computer Science this course involves elements of Formal Methods and Automated Reasoning. Formal Methods is concerned with proving properties of algorithms, specifying programming tasks and synthesizing programs from proofs. We will use formal methods tools such as interactive proof assistants (see [www.nuprl.org](http://www.nuprl.org)). We will also spend two weeks on constructive type theory, the language used by the Coq and Nuprl proof assistants.
|
||||
- [Syllabus](http://www.cs.cornell.edu/courses/CS4860/2012fa/schedule.php)
|
||||
@ -943,7 +948,7 @@ and anti-analysis techniques.
|
||||
- [Syllabus](http://courses2.cit.cornell.edu/cs5724/)
|
||||
- [Lectures](http://courses2.cit.cornell.edu/cs5724/schedule.htm)
|
||||
- [Assignments](http://courses2.cit.cornell.edu/cs5724/)
|
||||
- [CS 6452](http://www.cs.cornell.edu/courses/CS6452/2012sp/index.php) **Evolutionary Computation** *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" />
|
||||
- [CS 6452](http://www.cs.cornell.edu/courses/CS6452/2012sp/index.php) **Datacenter Networks and Services** *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" />
|
||||
- CS6452 focuses on datacenter networks and services. The emerging demand for web services and cloud computing have created need for large scale data centers. The hardware and software infrastructure for datacenters critically determines the functionality, performance, cost and failure tolerance of applications running on that datacenter. This course will examine design alternatives for both the hardware (networking) infrastructure, and the software infrastructure for datacenters.
|
||||
- [Syllabus](http://www.cs.cornell.edu/courses/CS6452/2012sp/lectures.php)
|
||||
- [Lectures](http://www.cs.cornell.edu/courses/CS6452/2012sp/lectures.php)
|
||||
@ -994,7 +999,7 @@ and anti-analysis techniques.
|
||||
- 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)
|
||||
- [14-740](http://www.ini740.com/S17/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://ini740.com/F17/) **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.
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user