computer-sciencealgorithmsbioinformaticscomputer-architecturecomputer-visiondatabase-systemsdatabasesembedded-systemsmachine-learningprogramming-languagequantum-computingroboticssecuritysystemsweb-development
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
22 KiB
22 KiB
Computer Science video courses
Introduction
List of Computer Science courses with video lectures. For more courses, please refer MIT OCW and awesome-courses
Focus would be to keep the list to the point in order keep it readable and usable. To access syllabus/notes/assignments, please visit link to the course or use Google search.
Table of Contents
- Introduction to Computer Science
- Data Structures and Algorithms
- Systems
- Database Systems
- Object Oriented Design and Software Engineering
- Artificial Intelligence
- Machine Learning
- Math for Computer Scientist
- Web Programming
- Theoretical CS and Programming Languages
- Computer Organization and Architecture
- Security
- Computer Graphics
- Misc
Courses
Introduction to Computer Science
- 6.00SC - Introduction to Computer Science and Programming (Spring 2011) - MIT OCW
- 6.00 - Introduction to Computer Science and Programming (Fall 2008) - MIT OCW
- 6.01SC - Introduction to Electrical Engineering and Computer Science I - MIT OCW
- 6.001 - Structure and Interpretation of Computer Programs, MIT (Textbook)
- CS 10 The Beauty & Joy of Computing, Spring 2015 - UCBerkeley
- CS 50 - Introduction to Computer Science, Harvard University
- CS 61A - Structure and Interpretation of Computer Programs [Python], UC Berkeley
- CS 101 - Computer Science 101, Stanford University (Register free to access Videos)
- CS 106A - Programming Methodology, Stanford University
- CS 106B - Programming Abstractions, Stanford University
- CS 107 - Programming Paradigms, Stanford University
Data Structures and Algorithms
- CS 61B - Data Structures, UC Berkeley
- 6.006 - Introduction to Algorithms, MIT OCW
- CS 161 - Design and Analysis of Algorithms, Prof. Tim Roughgarden, Stanford University
- CSE 373 - Analysis of Algorithms, Stony Brook - Prof Skiena
- 6.046J - Introduction to Algorithms - Fall 2005, MIT OCW
- 6.046 - Design and Analysis of Algorithms, Spring 2015 - MIT OCW
- Programming Challenges - Prof Skiena
- 16s-4102 - Algorithms, University of Virginia (Youtube)
- CS 170 Algorithms - Spring 2015 - UCBerkeley
- CS 261 - A Second Course in Algorithms, Stanford University (Lectures) (Youtube)
- CS 224 - Advanced Algorithms, Harvard University (Lecture Videos) (Youtube)
- ECS 122A - Algorithm Design and Analysis, UC Davis
- CS 6150 - Advanced Algorithms (Fall 2016), University of Utah
- ECS 222A - Graduate Level Algorithm Design and Analysis, UC Davis
- 6.851 - Advanced Data Structures, MIT (MIT OCW)
- 6.854 - Advanced Algorithms, MIT (Prof. Karger lectures)
Systems
- 6.033 Computer System Engineering - MIT
- CS 162 - Operating Systems and Systems Programming, UC Berkeley (Lectures - YouTube)
- CS 4414 - Operating Systems, University of Virginia
- CSE 421/521 - Introduction to Operating Systems, SUNY University at Buffalo, NY - Spring 2016 (Lectures - YouTube)
- CS 377 Fall 16: Operating Systems - Umass OS
- 6.828: Operating System Engineering [Fall 2014]
- VU:Distributed Systems: Principles and Paradigms by Maarten van Steen (Fall 2012), Vrije Universiteit, Amsterdam
- CS 677 Spring 16: Distributed Operating Systems - Umass OS
- CS 436: Distributed Computer Systems - U Waterloo
- 6.824: Distributed Systems, Spring 2015 - MIT
- CS194 Advanced Operating Systems Structures and Implementation, Spring 2013, UC Berkeley
- CPCS 663 - Real-Time Systems: Video Material - TAMU
- CS 251: Intermediate Software Design (C++ version)
- CS 251 (2015): Intermediate Software Design
- CS 282 (2014): Concurrent Java Network Programming in Android
- Distributed Algorithms, https://canvas.instructure.com/courses/902299
Database Systems
- CS 5530 - Database Systems, Spring 2016, University of Utah
- CSEP 544, Database Management Systems, Au 2015 - University of Washington
- 15-721 - Database Systems, CMU (Lectures - YouTube)
- CS 186 - Database Systems, UC Berkeley, Spring 2015 (Lectures- YouTube)
- CS 6530 - Graduate-level Database Systems, Fall 2016, University of Utah (Lectures - YouTube)
- 6.830/6.814: Database Systems [Fall 2014]
Object Oriented Design and Software Engineering
- ECE 462 Object-Oriented Programming using C++ and Java - Purdue
- Object Oriented Systems Analysis and Design (Systems Analysis and Design in a Changing World)
- Computer Science 169- Software Engineering - Spring 2015 - UCBerkeley
- Introduction to Service Design and Engineering - University of Trento, Italy
- OOSE: Software Dev Using UML and Java
- CS 411 - Software Architecture Design, Bilkent University
Artificial Intelligence
- CS 188 - Introduction to Artificial Intelligence, UC Berkeley
- 6.034 Artificial Intelligence, MIT OCW
Machine Learning
- StatLearning - Intro to Statistical Learning, Stanford University
- CS 156 - Learning from Data, Caltech
- 10-601 - Machine Learning, Carnegie Mellon University
- Microsoft Research - Machine Learning Course
- CS 446 - Machine Learning, Fall 2016, UIUC(Fall 2015 Lectures)
- undergraduate machine learning at UBC 2012, Nando de Freitas
- CS 229 - Machine Learning - Stanford University
- CS 5140/6140 - Data Mining, Spring 2016, University of Utah (Lectures - Youtube)
- CS 5350/6350 - Machine Learning, Fall 2016, University of Utah
- CS 6190 - Probabilistic Modeling, Spring 2016, University of Utah
- CS 6955 - Clustering, Spring 2015, University of Utah
- DS-GA 1008 - Deep Learning, New York University
- Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information
- Machine Learning 2013 - Nando de Freitas, UBC
- Machine Learning: 2014-2015, University of Oxford
- Deep learning at Oxford 2015 - Nando de Freitas
- 10-701 Machine Learning - Tom Mitchell, Spring 2011, Carnegie Mellon University (Fall 2014)
- 10-702/36-702 - Statistical Machine Learning - Larry Wasserman, Spring 2016, CMU (Spring 2015)
- 10-708 - Probabilistic Graphical Models, Carnegie Mellon University
- 10-725 Convex Optimization: Spring 2015 - CMU
- 10-801 Advanced Optimization and Randomized Algorithms
- 36-705 - Intermediate Statistics - Larry Wasserman, CMU
- CS 224d - Deep Learning for Natural Language Processing, Stanford University (Lectures - Youtube)
- CS 224N - Natural Language Processing, Stanford University
- CS 229r - Algorithms for Big Data, Harvard University (Youtube)
- CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University
- CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas
- Probabilistic Graphical Models, Daphne Koller, Stanford University
- Deep Learning, Stanford University
- Statistical Learning- Classification - University of Waterloo
- Deep Learning - University of Waterloo
- 9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT
- STA 4273H (Winter 2015): Large Scale Machine Learning
- CSEP 546, Machine Learning, Sp 2016 - University of Washington
- Machine Learning for Computer Vision - TUM
- Lecture: Variational Methods for Computer Vision (Prof. D. Cremers) TUM
- CAP 5415 - Computer Vision, University of Central Florida
Math for Computer Scientist
- 6.042J - Mathematics for Computer Science, Fall 2010, MIT OCW
- 6.042J - Mathematics for Computer Science, Spring 15, MIT OCW
- Computer Science 70, 001 - Fall 2012
- Probabilistic Systems Analysis and Applied Probability
- STATS 250 - Introduction to Statistics and Data Analysis, UMichigan
- 131B - Introduction to Probability and Statistics, UCI
- Statistics 110: Probability
- 18.06 - Linear Algebra, Prof. Gilbert Strang, MIT OCW
- Multiple View Geometry - Lecture 1 (Prof. Daniel Cremers) TUM
Web Programming
Theoretical CS and Programming Languages
- CS 164 Hack your language, UC Berkeley (Lectures - Youtube)
- CS 173 Programming Languages, Brown University (Book)
- CS 421 - Programming Languages and Compilers, UIUC (Videos)
- CSC 253 - CPython internals: A ten-hour codewalk through the Python interpreter source code, University of Rochester
- CSEP 501 - Compiler Construction, University of Washington (Lectures - Youtube)
- DMFP - Discrete Mathematics and Functional Programming, Wheaton College
- CS 374 - Algorithms & Models of Computation (Fall 2014), UIUC (Lecture videos)
- 6.045 Automata, Computability, and Complexity, MIT (Lecture Videos)
Computer Organization and Architecture
- 6.004 - Computation Structures Spring 2013, MIT
- CS 61C - Machine Structures, UC Berkeley (Lectures - YouTube)
- 18-447 - Introduction to Computer Architecture, CMU (Lectures - YouTube - Fall 15)
- 15-418 - Parallel Computer Architecture and Programming, CMU (Lecture Videos)
- EE445L Embedded Systems Design Lab, Fall 2015, UTexas
- CS149 Embedded Systems - Fall 2014 - UCBerkeley
Security
- 6.858 Computer Systems Security - MIT OCW
- CIS 4930/ CIS 5930 - Offensive Computer Security, Florida State University
- 18-636 Browser Security, Stanford
Computer Graphics
Misc
- CS 193a - Android App Development, Spring 2016, Stanford University
- Skiena's Computational Biology Lectures
- Skiena's Computational Finance Lectures
- AM 207 - Monte Carlo Methods and Stochastic Optimization, Harvard University
- CS 193p - Developing Applications for iOS, Stanford University
- CS 223A - Introduction to Robotics, Stanford University
- CS 3152 - Introduction to Computer Game Development, Cornell University
- Open Sourced Elective: Database and Rails - Intro to Ruby on Rails, University of Texas (Lectures - Youtube)
- SCICOMP - An Introduction to Efficient Scientific Computation, Universität Bremen (Lectures - Youtube)
- MIT CMS.611J Creating Video Games, Fall 2014
- Lecture: Visual Navigation for Flying Robots - TUM
- Image Processing and Analysis (Course) UC Davis