Awesome Courses

Algorithms Carnegie Mellon University

Algorithms University of Virginia

Introduction to Algorithms MIT

. It introduces students to the design of computer algorithms, as well as analysis of sophisticated algorithms.

Design and Analysis of Algorithms MIT

Advanced Data Structures MIT

Advanced Algorithms MIT

Advanced Algorithms MIT

Hacking a Google Interview MIT

course before attempting this one.

contains the calendar as well.

has been touted by many to be best for getting that job in Google. In addition, he's also well-known for tutoring students in competitive programming competitions. If you're looking to brush up your knowledge on Algorithms, you can't go wrong with this course.

Program & Data Representation University of Virginia

Advanced Algorithms Harvard University

A Second Course in Algorithms Stanford University

Fundamental Algorithms Univ of Illinois, Urbana-Champaign

Introduction to Analysis of Algorithms Cornell University

Data Structures UC Berkeley

Introduction to Competitive Programming Stanford University

Data Structures and Object Oriented Design University of Southern California (USC)

Software Design and Analysis I

Software Design and Analysis II CUNY Hunter College

Software Design and Analysis III

Software Design and Implementation University of Washington

Analysis of Algorithms Stony Brook University

in 2010, this course is an undergraduate introduction to algorithm design and analysis. It features traditional topics, such as Big Oh notation, as well as an importance on implementing specific algorithms. Also featured are sorting (in linear time), graph algorithms, depth-first search, string matching, dynamic programming, NP-completeness, approximation, and randomization.

Algorithm Design and Analysis UC Davis

Graduate Level Algorithm Design and Analysis UC Davis

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

The link to labs and projects is included in the website.

(Youtube)

(Youtube)

(Youtube)

Contains videos from sp2012 version, but there isn't much difference.

who has a Turing Award due to his contributions to algorithms. Course link includes a very comprehensive set of reference notes by Avrim Blum.

to access the problem set and lectures.

The Society of Mind MIT

Introduction to Artificial Intelligence UC Berkeley

Foundations of Artificial Intelligence Cornell University

Advanced Artificial Intelligence Cornell University

, to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality. It incorporates ideas from psychology, artificial intelligence, and computer science to resolve theoretical issues such as wholes vs. parts, structural vs. functional descriptions, declarative vs. procedural representations, symbolic vs. connectionist models, and logic

Great Ideas in Theoretical Computer Science MIT

Software Foundations University of Pennsylvania

Mathematical Foundations of Computing Stanford University

Discrete Structures Univ of Illinois Urbana-Champaign

Foundations of Cryptography UC Berkeley

Complexity Theory UC Berkeley

Data Structures and Functional Programming Cornell University

Introduction to Scientific Computing Cornell University

Algorithms & Models of Computation (Fall 2014) University of Illinois Urbana-Champaign

Information Retrieval Cornell University

Introduction to Theory of Computing Cornell University

Theory of Computing Cornell University

Programming Paradigms University of Arkansas (Fayetteville)

Written by the professor. Includes Instructor's Guide.

Computer Vision University of Central Florida

Computer Vision and Computational Photography University of Pennsylvania

Computer Graphics Carnegie Mellon University

3D Reconstruction with Computer Vision UTexas

Introduction to Computer Graphics Cornell University

Introduction to Computer Vision Cornell University

Computer Vision Cornell University

Introduction to Computer Graphics Brown University

Graduate Computer Graphics New York University

Structure and Interpretation of Computer Programs MIT

Software Construction, Fall 2016 MIT

The Beauty and Joy of Computing UC Berkeley

Computer Science 101 Stanford University

Programming Methodology Stanford University

Programming Abstractions Stanford University

Programming Paradigms Stanford University

Programming Practice Using Scala KAIST

Fundamental Programming Concepts Cornell University

Introduction to Computing Using Python Cornell University

Introduction to Computing Using Matlab Cornell University

Introduction to Computational Science and Engineering Using Matlab Graphical User Interfaces Cornell University

Transition to OO Programming Cornell University

Transition to Python Cornell University

and CS2420-20 Computer Science I and II for Hackers University of Utah

Object-Oriented Programming and Data Structures Cornell University

Web Information Systems Cornell University

Introduction to Computer Science Harvard University

Structure and Interpretation of Computer Programs [Python] UC Berkeley

Structure & Interpretation of Computer Programs [Racket] UC Berkeley

CS for All Harvey Mudd College

Programming Foundations I University of Arkansas (Fayetteville)

Understanding Computers and the Internet Harvard University Extension College

.

.

(one of the lead designers of Racket and author of HtDP). Mostly Racket and C, and a bit of Java, with explanations on how high level functional programming concepts relate to the design of OOP programs. Do this one before SICP if SICP is a bit too much...

(based on Scratch by MIT).

(epub, pdf)

Machine Learning Carnegie Mellon University

Probabilistic Graphical Models Carnegie Mellon University

Deep Learning Carnegie Mellon University

(slightly better)

which is a more approachable version of the Elements of Statistical Learning (or ESL) book.

available on Github.

Machine Learning Columbia University

Data Science Harvard University

Learning from Data Caltech

Introduction To Machine Learning UC Berkeley

Deep Learning for Natural Language Processing Stanford University

Algorithms for Big Data Harvard University

Convolutional Neural Networks for Visual Recognition Stanford University

Advanced Robotics UC Berkeley

Statistical and Discrete Methods for Scientific Computing University of Texas

Machine Learning Cornell University

Machine Learning for Data Science Cornell University

Tensorflow for Deep Learning Research Stanford University

Mining Massive Data Sets Stanford University

Information Retrieval and Web Search Stanford University

Convex Optimization Stanford University

Deep Learning for Natural Language Processing University of Oxford

Deep Learning New York University

Introduction to Matrix Methods Stanford University

Big Data Analytics & Advanced Big Data Analytics Columbia University

Deep Learning for Computer Vision and Natural Language Processing Columbia University

Fast.ai / University of San Francisco

Analyzing Big Data with Twitter UC Berkeley school of information

(Youtube)

University of Oxford

Reinforcement Learning in the Wild Yandex SDA

Intro to Statistical Learning Stanford University

and Lieven Vandenberghe are currently writing. Students will use a new language called Julia to do computations with matrices and vectors.

introduces topics in Machine Learning for both generative and discriminative estimation. Material will include least squares methods, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models, hidden Markov models, support vector machines, and kernel methods.

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

UvA Deep Learning Course University of Amsterdam

, it is now led by Zaid Harchaoui, although Prof. Lecun is rumored to still stop by from time to time. It covers the theory, technique, and tricks that are used to achieve very high accuracy for machine learning tasks in computer vision and natural language processing. The assignments are in Lua and hosted on Kaggle.

Fundamentals of Computer Networks CMU

Monte Carlo Methods and Stochastic Optimization Harvard University

Open Source Software Construction UC Riverside

Object Oriented System Design Stanford

Computer Networks UC Berkeley

Android App Development, Spring 2016 Stanford University

Developing Applications for iOS Stanford University

Introduction to Robotics Stanford University

Advanced Topics in Computer Systems UC Berkeley

Cutting-edge Web Technologies Berkeley

Introduction to Computer Game Development Cornell University

Software Architecture Design Bilkent University

Advanced Topics in Computer Game Development Cornell University

Analytics-driven Game Design Cornell University

Quantum Information Processing Cornell University

Applied Logic Cornell University

Intro to Game Developement Harvard University

Software Engineering Cornell University

Applications of Parallel Computers Cornell University

Computational Techniques for Analyzing Clinical Data Cornell University

Evolutionary Computation Cornell University

Datacenter Networks and Services Cornell University

Realistic Image Synthesis Cornell University

Computational Photography Cornell University

Computational Motion Cornell University

Algorithmic Game Theory Cornell University

Introduction to Game Development Tufts University

leaves off, focusing on the development of 2D and 3D interactive games. Students explore the design of such childhood games as Super Mario Bros., Legend of Zelda, and Portal in a quest to understand how video games themselves are implemented. Via lectures and hands-on projects, the course explores principles of 2D and 3D graphics, animation, sound, and collision detection using frameworks like Unity and LÖVE 2D, as well as languages like Lua and C#. By class’s end, students will have programmed

Web Programming University of Washington

GIS & Spatial Analysis UC Santa Barbara

(includes lecture materials and labs)

to download them.

Biologically Inspired Computation Indiana University

Software Engineering University of Hawaii

Humanitarian Free & Open Source Software Development Rochester Institute of Technology

, Ben Best, and Lisa Wedding

and for direct download

about the multi-disciplinary field algorithms inspired by naturally occurring phenomenon. This course provides introduces the following areas: L-systems, Cellular Automata, Emergence, Genetic Algorithms, Swarm Intelligence and Artificial Immune Systems. It's aim is to cover the fundamentals and enable readers to build up a proficiency in applying various algorithms to real-world problems.

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

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.

Intro to Ruby on Rails University of Texas

An Introduction to Efficient Scientific Computation Universität Bremen

). There is no longer an exam. However, if you have not already taken a decent undergrad OS class, you should talk with me before taking this class. The exam had the benefit of "paging in" the undergrad material, which may have been its primary value (since the pass rate was high).

). We will also spend two weeks on constructive type theory, the language used by the Coq and Nuprl proof assistants.

Adventures in Advanced Symbolic Programming MIT

Extensive programming assignments, using MIT/GNU Scheme. Students should have significant programming experience in Scheme, Common Lisp, Haskell, CAML or other "functional" language.

Introduction to Haskell Penn Engineering

Rust Programming UPenn

Introduction to Compilers Univ of Maryland

Principles of Programming Languages Politecnico di Milano - Lecture Notes - Readings

Functional Programming Princeton University

Compiler construction Stanford University

Hack your language! UC Berkeley

Programming Languages Brown University

Purely Functional Data Structures In Elm University of Chicago

Functional Systems in Haskell Stanford University

Data Structures and Functional Programming Cornell University

Introduction to Compilers Cornell University

Programming Languages and Compilers Univ of Illinois, Urbana-Champaign

Programming Languages Northeastern University

Programming Languages and Compilers University of Virginia

Network Programming Languages Cornell University

Scripting Languages Cornell University

Compilers University of Utah

Types and Semantics Cornell University

Functional Design and Programming San Diego State University

Principles of Compiler Design Swathmore College

Introduction to Programming Languages Swathmore College

CPython internals: A ten-hour codewalk through the Python interpreter source code University of Rochester

Programming Languages University of Washington

Compiler Construction University of Washington

Discrete Mathematics and Functional Programming Wheaton College

you ought to give this a shot. The course covers the design and implementation of compilers, and it explores related topics such as interpreters, virtual machines and runtime systems. Aside from the Prof's witty take on cheating the page has tons of interesting links on programming languages, parsing and compilers.

) and numerous other awesome books on programming languages. Uses a custom designed Pyret programming language to teach the concepts. There was an online class hosted in 2012, which includes all lecture videos for you to enjoy.

, this course teaches how to build a compiler in OCaml

Advanced Functional Programming University of Cambridge

, Lab2, Lab3

Practical Concurrent and Parallel Programming IT University of Copenhagen

semester also available, with more exercises

programming language & PAPL book to understand the fundamentals of programming languages.

Browser Security Stanford

Computer and Network Security MIT

Computer Systems Security MIT

Offensive Computer Security Florida State University

Computer and Network Security Stanford

Computer Security UC Berkeley

Security Modeling and Analysis Stanford

Internet/Network Security UC Berkeley

System Security Cornell University

Modern Binary Exploitation Rensselaer Polytechnic Institute

Malware Analysis Rensselaer Polytechnic Institute

Computer & Network Security University of Michigan

who has analyzed the security of Electronic Voting Machines in the US and over seas.

and Nickolai Zeldovich

to

and Xiuwen Liu. 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.

Applied Regression Methods Smith College

Introduction to Computer Systems (ICS) Carnegie-Mellon University

Cloud Computing (ICS) Carnegie-Mellon University

Operating System Design and Implementation Carnegie-Mellon University

Parallel Computer Architecture and Programming Carnegie-Mellon University

Distributed Systems Carnegie-Mellon University

Database Systems Carnegie-Mellon University

Database Systems Carnegie-Mellon University

Engineering Distributed Systems Carnegie-Mellon University

Introduction to Computer Architecture CMU

Computation Structures MIT

Distributed Systems MIT

Operating Systems MIT

Just do git clone git://g.csail.mit.edu/6.824-golabs-2014 6.824

is also a gem and recommended as a must read in Google's tutorial on Distributed System Design

Computer Organization & Systems Stanford University

Operating Systems Stanford University

Operating Systems and Systems Programming UC Berkeley

Introduction to the Internet: Architecture and Protocols UC Berkeley

GPU Programming Caltech

Introduction to Database Systems UC Berkeley

Unix Tools & Scripting Cornell University

Systems Programming (Spring 2016) Univ of Illinois, Urbana-Champaign

Computer System Organization and Programming Cornell University

Distributed Systems Univ of Illinois, Urbana-Champaign

Operating Systems Cornell University

Operating Systems University of Virginia

Real-Time Programming University of Waterloo

Cloud Computing Cornell University

Great Ideas in Computer Architecture (Machine Structures) UC Berkeley

Operating Systems University of Arkansas (Fayetteville) - An introduction to operating systems including topics in system structures, process management, storage management, files, distributed systems, and case studies.

Computer Architecture 3 CUNY Hunter College

UNIX System Programming (formerly UNIX Tools) CUNY Hunter College

Parallel Computing CUNY Hunter College

Operating Systems NYU

Distributed Systems University of Washington

Programming for Performance University of Waterloo

Embedded Systems using the Renesas RX63N Processor University of North Carolina at Charlotte

Introduction to Operating Systems SUNY University at Buffalo, NY

7 HWs with answer set as well

Spring 2015 lectures

Spring 2015 lectures

of a previous session are available to watch.

Principles of Distributed Computing ETH-Zurich

Parallelism and Concurrency Univ of Washington

Note: These are student recorded cam videos of the 2011 course. The videos explain a lot of concepts required for the labs and assignments.