Cs Video Courses
- Please check NOTES for general information about this list. - Please refer CONTRIBUTING.md for contribution guidelines. - Please feel free to raise any genuine issue you may have, however, it has been noticed that few people open empty issues to raise their GitHub contribution on their account. Su...
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| Registry ID | gh-tool--developer-y--cs-video-courses |
| Provider | github |
Cite this tool
Academic & Research Attribution
@misc{gh_tool__developer_y__cs_video_courses,
author = {Developer Y},
title = {Cs Video Courses Tool},
year = {2026},
howpublished = {\url{https://github.com/Developer-Y/cs-video-courses}},
note = {Accessed via Free2AITools Knowledge Fortress}
} 🔬Technical Deep Dive
Full Specifications [+]▾
⚡ Quick Commands
git clone https://github.com/Developer-Y/cs-video-courses pip install cs-video-courses 💬 Why this score?
The Nexus Index for Cs Video Courses aggregates Popularity (P:0), Velocity (V:0), and Credibility (C:0). The Utility score (U:0) represents deployment readiness, context efficiency, and structural reliability within the Nexus ecosystem.
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- Language
- Python
- License
- Open Source
- Version
- 1.0.0
Usage documentation not yet indexed for this tool.
🔗 View Source Code ↗Technical Documentation
Computer Science courses with video lectures
Introduction
- Please check NOTES for general information about this list.
- Please refer CONTRIBUTING.md for contribution guidelines.
- Please feel free to raise any genuine issue you may have, however, it has been noticed that few people open empty issues to raise their GitHub contribution on their account. Such spammers will be blocked.
- You are welcome to contribute, please create PR for actual college/University level courses. Please do not add links for small MOOCs, basic tutorials, or advertisements for some sites/channels.
Table of Contents
- Introduction to Computer Science
- Data Structures and Algorithms
- Systems Programming
- Database Systems
- Software Engineering
- Artificial Intelligence
- Machine Learning
- Computer Networks
- Math for Computer Scientist
- Web Programming and Internet Technologies
- Theoretical CS and Programming Languages
- Embedded Systems
- Real time system evaluation
- Computer Organization and Architecture
- Security
- Computer Graphics
- Image Processing and Computer Vision
- Computational Physics
- Computational Biology
- Quantum Computing
- Robotics and Control
- Computational Finance
- Network Science
- Blockchain Development
- Misc
Courses
Introduction to Computer Science
- CS 10 - The Beauty and Joy of Computing - Spring 2015 - Dan Garcia - UC Berkeley InfoCoBuild
- 6.0001 - Introduction to Computer Science and Programming in Python - MIT OCW
- 6.001 - Structure and Interpretation of Computer Programs, MIT
- Introduction to Computational Thinking - MIT
- CS 50 - Introduction to Computer Science, Harvard University (cs50.tv)
- CS50R - Introduction to Programming with R (Lecture Videos)
- CS50: Introduction to Computer Science with Python - Harvard (David J. Malan)
- CS 61A - Structure and Interpretation of Computer Programs [Python], UC Berkeley
- CPSC 110 - Systematic Program Design [Racket], University of British Columbia
- CS50's Understanding Technology
- CSE 142 Computer Programming I (Java Programming), Spring 2016 - University of Washington
- CS 1301 Intro to computing - Gatech
- CS 106A - Programming Methodology, Stanford University (Lecture Videos)
- CS 106B - Programming Abstractions, Stanford University (Lecture Videos)
- CS 106L - Standard C++ Programming(Lecture Videos)
- CS 106X - Programming Abstractions in C++ (Lecture Videos)
- CS 107 - Programming Paradigms, Stanford University
- CmSc 150 - Introduction to Programming with Arcade Games, Simpson College
- IN2377 - Concepts of C++ programming (Winter 2023), TUM (Winter 2022) (Summer 2022) (Summer 2021)
- IN1503 - Advanced C++ Programming, TUM
- LINFO 1104 - Paradigms of computer programming, Peter Van Roy, Université catholique de Louvain, Belgium - EdX
- FP 101x - Introduction to Functional Programming, TU Delft
- Introduction to Problem Solving and Programming - IIT Kanpur
- Introduction to programming in C - IIT Kanpur
- Programming in C++ - IIT Kharagpur
- Python Boot Camp Fall 2016 - Berkeley Institute for Data Science (BIDS)
- CS 101 - Introduction to Computer Science - Udacity
- 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
- Modern C++ Course (2018) - Bonn University
- Modern C++ (Lecture & Tutorials, 2020, Vizzo & Stachniss) - University of Bonn
- UW Madison CS 368 C++ for Java Programmers Fall 2020, by Michael Doescher
- UW Madison CS 354 Machine Organization and Programming spring 2020, 2021, by Michael Doescher
- Cornell CS 1110 Introduction to Computing using Python fall 2020, by Walker White (Lecture Videos)
- Cornell ECE 4960 Computational and Software Engineering spring 2017, by Edwin Kan
Data Structures and Algorithms
- ECS 36C - Data Structures and Algorithms (C++) - Spring 2020 - Joël Porquet-Lupine - UC Davis
- Programming and Data Structures with Python, 2021-2022, Sem I - by Prof. Madhavan Mukund, CMI
- Graph Algorithms - Robert Sedgewick - Princeton University
- EECS 477 - Introduction to Algorithms, Winter 2023, UMichigan
- EECS 498 / 598 - Advanced Graph Algorithms: Graph Algorithms via Graph Decomposition, Fall 2025, UMichigan
- EECS 498 / 598 - Advanced Graph Algorithms: Expanders and Fast Graph Algorithms, Fall 2021, UMichigan
- 6.006 - Introduction to Algorithms, MIT OCW
- MIT 6.006 Introduction to Algorithms, Spring 2020
- Algorithms: Design and Analysis 1 - Stanford University
- Algorithms: Design and Analysis 2 - Stanford University
- COS 226 Algorithms, Youtube, Princeton - by Robert Sedgewick and Kevin Wayne
- CSE 331 Introduction to Algorithm Design and Analysis, SUNY University at Buffalo, NY - Fall 2017 (Lectures) (Homework Walkthroughs)
- CSE 373 - Analysis of Algorithms, Stony Brook - Prof Skiena
- COP 3530 Data Structures and Algorithms, Prof Sahni, UFL (Videos)
- CS225 - Data Structures - University of Illinois at Urbana-Champaign(Video lectures)
- CS2 - Data Structures and Algorithms - Richard Buckland - UNSW
- Data Structures - Pepperdine University
- CS 161 - Design and Analysis of Algorithms, Prof. Tim Roughgarden, Stanford University
- 6.046J - Introduction to Algorithms - Fall 2005, MIT OCW
- Introduction to Algorithms (Spring 2020), MIT OCW
- 6.046 - Design and Analysis of Algorithms, Spring 2015 - MIT OCW
- CS 473 - Algorithms - University of Illinois at Urbana-Champaign (Notes - Jeff Erickson) (YouTube)
- COMP300E - Programming Challenges, Prof Skiena, Hong Kong University of Science and Technology - 2009
- 16s-4102 - Algorithms, University of Virginia (Youtube)
- CS 61B - Data Structures (Java) - UC Berkeley(Discussion 2022)
- CS 170 Algorithms - UCBerkeley Fall 2019, Youtube Fall 2018, Youtube Fall 2018,Bilibili 2013 Bilibili
- CS 159 Data-Driven Algorithm Design - Caltech Spring 2020, Youtube
- ECS 122A - Algorithm Design and Analysis, UC Davis
- CSE 373 - Data Structures and Algorithms, Winter 2024 - University of Washington (Winter 2024, Youtube) (Spring 2023, Notes) (Spring 2023, Youtube)
- CSEP 521 - Applied Algorithms, Winter 2013 - University of Washington (Videos)
- Data Structures And Algorithms - IIT Delhi
- Design and Analysis of Algorithms - IIT Bombay
- Programming, Data Structures and Algorithms - IIT Madras
- Design and Analysis of Algorithms - IIT Madras
- Fundamental Algorithms:Design and Analysis - IIT Kharagpur
- Programming and Data Structure - IIT Kharagpur
- Programming, Data structures and Algorithms - IIT Madras
- Programming, Data Structures and Algorithms in Python - IIT Madras
- Programming and Data structures (PDS) - IIT Madras
- COP 5536 Advanced Data Structures, Prof Sahni - UFL (Videos)
- CS 261 - A Second Course in Algorithms, Stanford University (Youtube)
- CS 224 - Advanced Algorithms, Harvard University (Lecture Videos) (Youtube)
- CS 6150 - Advanced Algorithms (Fall 2016), University of Utah
- CS 6150 - Advanced Algorithms (Fall 2017), 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)
- CS264 Beyond Worst-Case Analysis, Fall 2014 - Tim Roughgarden Lecture (Youtube)
- CS364A Algorithmic Game Theory, Fall 2013 - Tim Roughgarden Lectures
- CS364B Advanced Mechanism Design, Winter 2014 - Tim Roughgarden Lectures
- Algorithms - Aduni
- 6.889 - Algorithms for Planar Graphs and Beyond (Fall 2011) MIT
- 6.890 Algorithmic Lower Bounds: Fun with Hardness Proofs - MIT OCW
- Computer Algorithms - 2 - IIT Kanpur
- Parallel Algorithm - IIT Kanpur
- Graph Theory - IISC Bangalore
- Data Structures - mycodeschool
- Algorithmic Game Theory, Winter 2020/21 - Uni Bonn
- NETS 4120: Algorithmic Game Theory, Spring 2023 - UPenn
- Introduction to Game Theory and Mechanism Design - IIT Kanpur
- 15-850 Advanced Algorithms - CMU Spring 2023
- CS 270. Combinatorial Algorithms and Data Structures, Spring 2021 (Youtube)
- CMU 15 850 Advanced Algorithms spring 2023, by Anupam Gupta
- UC Berkeley CS 294-165 Sketching Algorithms fall 2020, by Jelani Nelson (Youtube)
- UIUC CS 498 ABD / CS 598 CSC Algorithms for Big Data fall 2020, by Chandra Chekuri
- Algorithms for Data Science spring 2021, by Anil Maheshwari
- CMU 15 859 Algorithms for Big Data fall 2020, by David Woodruff
- CO 642 Graph Theory - University of Waterloo
- COMS W4241 Numerical Algorithms spring 2006, by Henryk Wozniakowski - Columbia
- Bonn Algorithms and Uncertainty summer 2021, by Thomas Kesselheim
- Harvard Information Theory 2022, by Gregory Falkovich
- Math 510 - Linear Programming and Network Flows - Colorado State University
- LINFO 2266 Advanced Algorithms for Optimization 2021, by Pierre Schaus - UCLouvain
- MIT 6.5210 / 6.854 / 18.415 Advanced Algorithms Fall 2013, 2020, 2021, 2022, by David Karger (Spring 2016, by Ankur Moitra)
- CMU 10 801 Advanced Optimization and Randomized Algorithms spring 2014, by Suvrit Sra and Alex Smola
- Purdue CS 381 Fundamental Algorithms, by Kent Quanrud (Spring 2022)
- Purdue CS 390 ATA Fundamental Algorithms Advanced, by Kent Quanrud (Spring 2025)
- Purdue CS 580 Graduate Algorithms, by Kent Quanrud (Spring 2023) (Spring 2024)
- Purdue CS 588 Randomized Algorithms, by Kent Quanrud (Fall 2022) (Spring 2024)
- UC Santa Cruz CSE 101 Intro to Data Structures and Algorithms fall 2022, by Seshadhri Comandur (Fall 2020)
- UC Santa Cruz CSE 201 Analysis of Algorithms winter 2022, by Seshadhri Comandur
- UC Santa Cruz CSE 202 Combinatorial Algorithms spring 2021, by Seshadhri Comandur
- UC Santa Cruz CSE 104, 204 Computational Complexity spring 2022, by Seshadhri Comandur (Fall 2020)
- UC Santa Cruz CSE 290A Randomized Algorithms spring 2020, by Seshadhri Comandur
- University of Maryland CMSC351 Introduction to Algorithms, by Mohammad Hajiaghayi
- University of Maryland CMSC858F Network Algorithms and Approximations, by Mohammad Hajiaghayi (YouTube playlists)
- University of Maryland CMSC858M Algorithmic Lower Bounds: Fun with Hardness Proofs, by Mohammad Hajiaghayi (YouTube playlists)
- University of Maryland UMD DATA602 / MSML602 Principles of Data Science spring 2024, by Mohammad Hajiaghayi
- Algorithms for Big-Data (Fall 2020) - Saket Saurabh
- CS498ABD - Algorithms for Big Data - UIUC, Fall 2020
- Advanced Data Structures
- CS60025 Algorithmic Game Theory - IIT KGP - Winter 2020
- CS60083 Parameterized Algorithms - IIT KGP
- Parameterized Complexity
- Structural Graph Theory - IIT Madras
- Information Theory - IISC Bangalore
Systems Programming
- 15-213 Introduction to Computer Systems, Fall 2015 - CMU
- Computer Systems: A programmer's Perspective
- CS361 - COMPUTER SYSTEMS - UIC
- CS 3650 - Computer Systems - Fall 2020 - Nat Tuck - NEU (Lectures - YouTube)
- CS 4400 – Computer Systems Fall 2016 - UoUtah
- Systems - Aduni
- CS110: Principles of Computer Systems - Stanford
Operating Systems
- APS 105 - Computer Fundamentals - Winter 2025 - Jon Eyolfson - University of Toronto (Winter 2024)
- ECS 150 - Operating Systems and Systems Programming - Fall 2020 - Joël Porquet-Lupine - UC Davis
- ECE 344 - Operating Systems - Fall 2024 - Jon Eyolfson - University of Toronto (Fall 2024 Section 2) (Fall 2023) (Fall 2022)
- ECE 353 - Systems Software - Winter 2025 - Jon Eyolfson - University of Toronto (Winter 2024) (Winter 2023)
- ECE 454 - Computer Systems Programming - Fall 2024 - Jon Eyolfson - University of Toronto
- CS124 Operating Systems - California Institute of Technology, Fall 2018 - Youtube
- CS 162 Operating Systems and Systems Programming, Spring 2015 - University of California, Berkeley (Fall 2020 - YouTube)
- CS 4414 - Operating Systems, University of Virginia (rust-class)
- CS 4414 Operating Systems, Fall 2018 - University of Virginia
- CSE 421/521 - Introduction to Operating Systems, SUNY University at Buffalo, NY - Spring 2016 (Lectures - YouTube) (Recitations 2016) (Assignment walkthroughs)
- CS 377 - Operating Systems, Fall 16 - Umass OS
- CS 577 - Operating Systems, Spring 20 - Umass OS
- 6.828 - Operating System Engineering [Fall 2014]
- 6.S081 - Operating System Engineering [Fall 2020]
- CSE 30341 - Operating Systems, Spr 2008
- CSEP 551 Operating Systems Autumn 2014 - University of Washington
- Introduction to Operating Systems - IIT Madras
- CS194 Advanced Operating Systems Structures and Implementation, Spring 2013 InfoCoBuild, UC Berkeley
- CSE 60641 - Graduate Operating Systems, Fall 08
- Advanced Programming in the UNIX Environment
- Operating System - IIT Madras
Distributed Systems
- CS 677 - Distributed Operating Systems, Spring 24 - Umass OS
- CS 436 - Distributed Computer Systems - U Waterloo
- 6.824 - Distributed Systems, Spring 2015 - MIT
- 6.824 Distributed Systems - Spring 2020 - MIT (Youtube)
- Distributed Systems Lecture Series
- Distributed Algorithms, https://canvas.instructure.com/courses/902299
- CSEP 552 - PMP Distributed Systems, Spring 2013 - University of Washington (Videos)
- CSE 490H - Scalable Systems: Design, Implementation and Use of Large Scale Clusters, Autumn 2008 - University of Washington (Videos)
- MOOC - Cloud Computing Concepts - UIUC
- Distributed Systems (Prof. Pallab Dasgupta)
- EdX KTHx ID2203 Reliable Distributed Algorithms
- Distributed Data Management - Technische Universität Braunschweig, Germany
- Information Retrieval and Web Search Engines - Technische Universität Braunschweig, Germany
- Middleware and Distributed Systems (WS 2009/10) - Dr. Martin von Löwis - HPI
- CSE 138 - Distributed Systems - UC Santa Cruz, Spring 2020 (2021)
- CMU 15 440 / 640 Distributed Systems Spring 2022, by Mahadev Satyanarayanan, Padmanabhan Pillai
- UNC Comp533 - Distributed Systems Spring 2020
- Brown CSCI 1380 Distributed Computer Systems spring 2016, by Tom Doeppner & Rodrigo Fonseca
- Distributed Systems lecture series - Martin Kleppmann
- Distributed Algorithms - Jukka Suomela
- Programming Parallel Computers - Jukka Suomela
Real-Time Systems
- 6.172 Performance Engineering of Software Systems - MIT OCW
- Performance Evaluation of Computer Systems - IIT Madras
- Storage Systems - IISC Bangalore
- MAP6264 - Queueing Theory - FAU(Video Lectures)
- EE 380 Colloquium on Computer Systems - Stanford University (Lecture videos)
Database Systems
- CMPSC 431W Database Management Systems, Fall 2015 - Penn State University Lectures - YouTube
- CS121 - Introduction to Relational Database Systems, Fall 2016 - Caltech
- CS 5530 - Database Systems, Spring 2016 - University of Utah
- Distributed Data Management (WT 2018/19) - HPI University of Potsdam
- MOOC - Database Stanford Dbclass
- CSEP 544, Database Management Systems, Au 2015 - University of Washington
- Database Design - IIT Madras
- Fundamentals of Database Systems - IIT Kanpur
- Principles of Database Management, Bart Baesens
- FIT9003 Database Systems Design - Monash University
- 15-445 - Introduction to Database Systems, CMU (YouTube-2017), (YouTube-2018),(YouTube-2019), (YouTube-2021), (YouTube-2022),(YouTube-2023),(YouTube-2024),(YouTube-2025)
- 15-721 - Advanced Database Systems, CMU (YouTube-2024, YouTube-2023, YouTube-2022)
- CS122 - Relational Database System Implementation, Winter 2014-2015 - Caltech
- CS 186 - Database Systems, UC Berkeley, Spring 2015
- CS 6530 - Graduate-level Database Systems, Fall 2016, University of Utah (Lectures - YouTube)
- 6.830/6.814 - Database Systems Fall 2014
- Informatics 1 - Data & Analysis 2014/15- University of Edinburgh
- Database Management Systems, Aduni
- D4M - Signal Processing on Databases
- In-Memory Data Management (2013)Prof. Hasso Plattner - HPI
- Distributed Data Management (WT 2019/20) - Dr. Thorsten Papenbrock - HPI
- CS122d - NoSQL Data Management (Spring 21) - Prof. Mike Carey - UC Irvine
Software Engineering
Object Oriented Design
- ECE 462 Object-Oriented Programming using C++ and Java - Purdue
- Object-oriented Program Design and Software Engineering - Aduni
- OOSE - Object-Oriented Software Engineering, Dr. Tim Lethbridge
- Object Oriented Systems Analysis and Design (Systems Analysis and Design in a Changing World)
- CS 251 - Intermediate Software Design (C++ version) - Vanderbilt University
- OOSE - Software Dev Using UML and Java
- Object-Oriented Analysis and Design - IIT Kharagpur
- CS3 - Design in Computing - Richard Buckland UNSW
- Informatics 1 - Object-Oriented Programming 2014/15- University of Edinburgh
- Software Engineering with Objects and Components 2015/16- University of Edinburgh
Software Engineering
- Computer Science 169- Software Engineering - Spring 2015 - UCBerkeley
- Computer Science 169- Software Engineering - Fall 2019 - UCBerkeley
- CS 5150 - Software Engineering, Fall 2014 - Cornell University
- Introduction to Service Design and Engineering - University of Trento, Italy
- CS 164 Software Engineering - Harvard
- System Analysis and Design - IISC Bangalore
- Software Engineering - IIT Bombay
- Dependable Systems (SS 2014)- HPI University of Potsdam
- Automated Software Testing - ETH Zürich | Spring 2024
- Software Testing - IIT Kharagpur
- Software Testing - Udacity, course-cs258 | 2015
- Software Debugging - Udacity, course-cs259 | 2015
- Software Engineering - Bauhaus-Uni Weimar
- CMU 17-445 Software Engineering for AI-Enabled Systems summer 2020, by Christian Kaestner
Software Architecture
Concurrency
- CS176 - Multiprocessor Synchronization - Brown University (Videos from 2012)
- CS 282 (2014): Concurrent Java Network Programming in Android
- CSE P 506 – Concurrency, Spring 2011 - University of Washington (Videos)
- CSEP 524 - Parallel Computation - University of Washington (Videos)
- Parallel Programming Concepts (WT 2013/14) - HPI University of Potsdam
- Parallel Programming Concepts (WT 2012/13) - HPI University of Potsdam
- UIUC ECE 408 / CS 408 Applied Parallel Programming fall 2022, by Wen-mei Hwu, Sanjay Patel (Spring 2018)
- UIUC ECE 508 / CS 508 Manycore Parallel Algorithms spring 2019, by Wen-mei Hwu
- UIUC CS 420 / ECE 492 / CSE 402 Introduction to Parallel Programming for Scientists and Engineers fall 2015, by Sanjay Kale
- Stanford CME 213 Introduction to Parallel Computing using MPI, openMP, and CUDA winter 2020, by Eric Darve
Mobile Application Development
- MOOC Programming Mobile Applications for Android Handheld Systems - University of Maryland
- CS 193p - Developing Applications for iOS, Stanford University
- CS S-76 Building Mobile Applications - Harvard
- CS 251 (2015): Intermediate Software Design
- Android App Development for Beginners Playlist - thenewboston
- Android Application Development Tutorials - thenewboston
- MOOC - Developing Android Apps - Udacity
- MOOC - Advanced Android App Development - Udacity
- CSSE490 Android Development Rose-Hulman Winter 2010-2011, Dave Fisher
- iOS Course, Dave Fisher
- Developing iPad Applications for Visualization and Insight - Carnegie Mellon University
- Mobile Computing - IIT Madras
- Mobile Information Systems - Bauhaus-Uni Weimar
Artificial Intelligence
- CS50 - Introduction to Artificial Intelligence with Python (and Machine Learning), Harvard OCW
- CS 188 - Introduction to Artificial Intelligence, UC Berkeley - Spring 2025, by John Canny, Oliver Grillmeyer (Spring 2024) (Spring 2023)
- 6.034 Artificial Intelligence, MIT OCW
- CS221: Artificial Intelligence: Principles and Techniques - Autumn 2019 - Stanford University
- 15-780 - Graduate Artificial Intelligence, Spring 14, CMU
- CSE 592 Applications of Artificial Intelligence, Winter 2003 - University of Washington
- CS322 - Introduction to Artificial Intelligence, Winter 2012-13 - UBC (YouTube)
- CS 4804: Introduction to Artificial Intelligence, Fall 2016
- CS 5804: Introduction to Artificial Intelligence, Spring 2015
- Artificial Intelligence, Fall 2023 - FAU (Spring 2023) (Fall 2022) (Spring 2021) (Fall 2020) (Fall 2018) (Spring 2018)
- Artificial Intelligence - IIT Kharagpur
- Artificial Intelligence - IIT Madras
- Artificial Intelligence(Prof.P.Dasgupta) - IIT Kharagpur
- MOOC - Intro to Artificial Intelligence - Udacity
- MOOC - Artificial Intelligence for Robotics - Udacity
- Graduate Course in Artificial Intelligence, Autumn 2012 - University of Washington
- Agent-Based Systems 2015/16- University of Edinburgh
- Informatics 2D - Reasoning and Agents 2014/15- University of Edinburgh
- Artificial Intelligence - Hochschule Ravensburg-Weingarten
- Deductive Databases and Knowledge-Based Systems - Technische Universität Braunschweig, Germany
- Artificial Intelligence: Knowledge Representation and Reasoning - IIT Madras
- Semantic Web Technologies by Dr. Harald Sack - HPI
- Knowledge Engineering with Semantic Web Technologies by Dr. Harald Sack - HPI
- T81-558: Applications of Deep Neural Networks by Jeff Heaton, 2022, Washington University in St. Louis
- MSU programming for AI
Machine Learning
Introduction to Machine Learning
- Introduction to Machine Learning for Coders
- MOOC - Statistical Learning, Stanford University
- Statistical Learning with Python - Stanford Online
- Foundations of Machine Learning Boot Camp, Berkeley Simons Institute
- CS 155 - Machine Learning & Data Mining, 2023 - Caltech (Notes-2020) (YouTube-2020) (Notes-2019) (YouTube-2019) (Notes-2018) (YouTube-2018) (Notes-2017) (YouTube-2017) (Notes-2016) (YouTube-2016)
- CS 156 - Learning from Data, Caltech
- 10-601 - Introduction to Machine Learning (MS) - Tom Mitchell - 2015, CMU (YouTube)
- 10-601 Machine Learning | CMU | Fall 2017
- 10-701 - Introduction to Machine Learning (PhD) - Tom Mitchell, Spring 2011, CMU (Fall 2014) (Spring 2015 by Alex Smola) (Fall 2020 by Ziv Bar-Joseph, Eric Xing)
- 10 - 301/601 - Introduction to Machine Learning - Fall 2023 - CMU
- 6.036 - Machine Learning, Broderick - MIT Fall 2020
- Mediterranean Machine Learning summer school 2024 (YouTube-2023) (YouTube-2022) (YouTube-2021)
- LxMLS Lisbon Machine Learning School 2024 (YouTube-2023) (YouTube-2022) (YouTube-2021) (YouTube-2020)
- Applied Machine Learning (Cornell Tech CS 5787, Fall 2020)
- Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati) (Spring 2022)
- CMS 165 Foundations of Machine Learning - 2019 - Caltech (Youtube)
- CMS 165 Foundations of Machine Learning and Statistical Inference - 2020 - Caltech
- Microsoft Research - Machine Learning Course
- CS 446 - Machine Learning, Fall 2016, UIUC
- CS 582 - Machine Learning for Bioinformatics, Fall 2024, UIUC
- CMPUT 267 Machine Learning - Fall 2024 - University of Alberta (Youtube)
- ECE 364 - Programming Methods for Machine Learning, Spring 2025, UIUC
- undergraduate machine learning at UBC 2012, Nando de Freitas
- CS 229 - Machine Learning - Stanford University (Autumn 2018)
- CS 189/289A Introduction to Machine Learning, Prof Jonathan Shewchuk - UCBerkeley
- CPSC 340: Machine Learning and Data Mining (2018) - UBC
- CS391L Machine Learning, Spring 2025 - UT Austin
- CS4780/5780 Machine Learning, Fall 2013 - Cornell University
- CS4780/5780 Machine Learning, Fall 2018 - Cornell University (Youtube)
- CSE474/574 Introduction to Machine Learning - SUNY University at Buffalo
- CS 5350/6350 - Machine Learning, Spring 2024, University of Utah (Youtube)
- ECE 4252/8803 Fundamentals of Machine Learning (FunML), Spring 2024 - Georgia Tech
- ECE 5984 Introduction to Machine Learning, Spring 2015 - Virginia Tech
- CSx824/ECEx242 Machine Learning, Bert Huang, Fall 2015 - Virginia Tech
- STA 4273H - Large Scale Machine Learning, Winter 2015 - University of Toronto
- CSC 2515 Introduction to Machine Learning, Amir-massoud Farahmand, Fall 2021, University of Toronto
- ECE 421 Introduction to Machine Learning, Amir Ashouri, Winter 2019, University of Toronto
- EECS 4404E/5327 Introduction to Machine Learning, Amir Ashouri, Fall 2019, York University
- CS 480/680 Introduction to Machine Learning, Gautam Kamath, University of Waterloo (Spring 2021)
- CS 480/680 Introduction to Machine Learning, Kathryn Simone, University of Waterloo (Fall 2024)
- CS 485/685 Machine Learning, Shai Ben-David, University of Waterloo
- STAT 441/841 Classification Winter 2017 , Waterloo
- 10-605 - Machine Learning with Large Datasets, Fall 2016 - CMU
- Information Theory, Pattern Recognition, and Neural Networks - University of Cambridge
- Pattern Analysis (2018) - FAU (Class 2017) (Class 2016) (Class 2015) (Class 2009)
- Pattern Recognition (2020-2021) - FAU (Class 2012-2013)
- Beyond the Patterns (2020-2021) - FAU
- Python and machine learning - Stanford Crowd Course Initiative
- MOOC - Machine Learning Part 1a - Udacity/Georgia Tech (Part 1b Part 2 Part 3)
- Pattern Recognition Class (2012)- Universität Heidelberg
- Introduction to Machine Learning and Pattern Recognition - CBCSL OSU
- Introduction to Machine Learning - IIT Kharagpur
- Introduction to Machine Learning - IIT Madras
- Pattern Recognition - IISC Bangalore
- Pattern Recognition and Application - IIT Kharagpur
- Pattern Recognition - IIT Madras
- Machine Learning Summer School 2013 - Max Planck Institute for Intelligent Systems Tübingen
- Machine Learning - Professor Kogan (Spring 2016) - Rutgers
- CS273a: Introduction to Machine Learning (YouTube)
- Machine Learning Crash Course 2015
- COM4509/COM6509 Machine Learning and Adaptive Intelligence 2015-16
- Introduction to Machine Learning - Spring 2018 - ETH Zurich
- Machine Learning - Pedro Domingos- University of Washington
- CSE 446/546 - Machine Learning, Spring 2020 - University of Washington (Videos)
- Machine Learning (COMP09012)
- Probabilistic Machine Learning 2020 - University of Tübingen
- Statistical Machine Learning 2020 - Ulrike von Luxburg - University of Tübingen
- COMS W4995 - Applied Machine Learning - Spring 2020 - Columbia University
- Machine Learning for Engineers 2022 (YouTube)
- 10-418 / 10-618 (Fall 2019) Machine Learning for Structured Data
- ORIE 4741/5741: Learning with Big Messy Data - Cornell
- Machine Learning in IoT
- Stanford CS229M: Machine Learning Theory - Fall 2021
- Intro to Machine Learning and Statistical Pattern Classification - Prof Sebastian Raschka
- CMU's Multimodal Machine Learning course (11-777), Fall 2020
- EE104: Introduction to Machine Learning - Stanford University
- CPSC 330: Applied Machine Learning (2020) - UBC
- Machine Learning 2013 - Nando de Freitas, UBC
- Machine Learning, 2014-2015, University of Oxford
- 10-702/36-702 - Statistical Machine Learning - Larry Wasserman, Spring 2016, CMU (Spring 2015)
- 10-715 Advanced Introduction to Machine Learning - CMU (YouTube)
- CS 281B - Scalable Machine Learning, Alex Smola, UC Berkeley
- 100 Days of Machine Learning - CampusX (Hindi)
- CampusX Data Science Mentorship Program 2022-23 (Hindi)
- Statistical Machine Learning - S2023 - Benyamin Ghojogh
- MIT 6.5940 EfficientML.ai Lecture, Fall 2023
- TinyML - Tiny Machine Learning at UPenn
- ECE 4760 (Digital Systems Design Using Microcontrollers) at Cornell for the Fall, 2022 (Spring 2021)
- EfficientML.ai Lecture, Fall 2023, MIT 6.5940
- SFU CMPT 727 Statistical Machine Learning, by Maxwell Libbrecht (Spring 2023) (Spring 2022)
- UC Berkeley CS 189 / 289A Introduction to Machine Learning fall 2023, by Jennifer Listgarten & Jitendra Malik
- UC Berkeley CS 189 Introduction to Machine Learning (CDSS offering) spring 2022, by Marvin Zhang
- UC San Diego/edX DSE 220X Machine Learning Fundamentals, by Sanjoy Dasgupta
- MIT 6.036 Introduction to Machine Learning spring 2019, by Leslie Kaelbling
- LMU Munich Introduction to Machine Learning
- CMU 15 388 / 15 688 Practical Data Science, by Zico Kolter (Fall 2019) (Spring 2018)
- UW Madison CS 320 Data Programming II spring 2021, by Tyler R. Caraza-Harter
- UC San Diego COGS9 Introduction to Data Science fall 2020, by Jason Fleischer
- UCLA Stats 15 Introduction to Data Science fall 2022, by Miles Chen
- UCLA Stats 21 Python and Other Technologies for Data Science spring 2024, by Miles Chen (Spring 2021)
- UCLA Stats C161/C261 Introduction to Pattern Recognition and Machine Learning winter 2024, by Arash Amini (Winter 2023)
- UCLA Stats 231C Theories of Machine Learning spring 2022, by Arash Amini
- MSU Machine Learning
- Data Science for Dynamical Systems, by Oliver Wallscheid & Sebastian Peitz (YouTube)
- Cambridge Statistical Learning in Practice 2021, by Alberto J. Coca
- Data 8: The Foundations of Data Science - UC Berkeley (Spring 23) (Fall 22) (Spring 22) (Summer 17)
- Data 144: Foundations of Data Science spring 2021 - Vassar College (Course materials)
- CSE519 - Data Science Fall 2016 - Skiena, SBU
- CS 109 Data Science, Harvard University (YouTube)
- 6.0002 Introduction to Computational Thinking and Data Science - MIT OCW
- Data 100: Principles and Techniques of Data Science - UC Berkeley (Fall 25) (Fall 24) (Spring 24) (Summer 19)
- Data 102 - Spring 21- UC Berkeley (YouTube)
- Distributed Data Analytics (WT 2017/18) - HPI University of Potsdam
- Data Profiling and Data Cleansing (WS 2014/15) - HPI University of Potsdam
- CS 229r - Algorithms for Big Data, Harvard University (Youtube)
- Algorithms for Big Data - IIT Madras
- Python Data Science with the TCLab (YouTube)
- Foundations of Data Analysis (Fall 2020)- University of Utah
Data Mining
- CSEP 546, Data Mining - Pedro Domingos, Sp 2016 - University of Washington (YouTube)
- CS 5140/6140 - Data Mining, Spring 2020, University of Utah by Prof. Jeff Phillips (Youtube)
- CS 5140/6140 - Data Mining, Spring 2023, University of Utah by Prof. Ana Marasović (Youtube)
- CS 5955/6955 - Data Mining, University of Utah (YouTube)
- Statistics 202 - Statistical Aspects of Data Mining, Summer 2007 - Google (YouTube)
- MOOC - Text Mining and Analytics by ChengXiang Zhai
- Information Retrieval SS 2014, iTunes - HPI
- MOOC - Data Mining with Weka
- CS 290 DataMining Lectures
- CS246 - Mining Massive Data Sets, Winter 2016, Stanford University (YouTube)
- Information Retrieval - Spring 2018 - ETH Zurich
- Information Retrieval - WS 2022/23 - Universität Freiburg
- CAP6673 - Data Mining and Machine Learning - FAU(Video lectures)
- CS 412 - Introduction to Data Mining - UIUC
- CS 512 - Data Mining Principles - UIUC (YouTube)
Probabilistic Graphical Modeling
Deep Learning
- Full Stack Deep Learning - Course 2022
- Full Stack Deep Learning - Course 2021
- NYU Deep Learning Spring 2020
- NYU Deep Learning Spring 2021
- 6.S191: Introduction to Deep Learning - MIT
- 15.773: Hands-On Deep Learning Spring 2024 - MIT
- 6.7960: Deep Learning Fall 2024 - MIT
- Intro to Deep Learning and Generative Models Course - Prof Sebastian Raschka
- Deep Learning CMU
- CS231n Deep Learning for Computer Vision - Stanford University (Spring 2025) (Winter 2016 Andrej Karpathy)
- Deep Learning: CS 182 Spring 2021
- 10-414/714: Deep Learning Systems - CMU (Youtube)
- 11-785: Introduction to Deep Learning - CMU (Lectures - YouTube-2024, Recitations - YouTube-2024)
- Part 1: Practical Deep Learning for Coders, v3 - fast.ai
- Part 2: Deep Learning from the Foundations - fast.ai
- Deep learning at Oxford 2015 - Nando de Freitas
- Self-Driving Cars — Andreas Geiger, 2021/22 (YouTube)
- 6.S094: Deep Learning for Self-Driving Cars - MIT
- CS294-129 Designing, Visualizing and Understanding Deep Neural Networks (YouTube)
- CS230: Deep Learning - Autumn 2018 - Stanford University
- CS230: Deep Learning - Autumn 2025 - Stanford University
- STAT-157 Deep Learning 2019 - UC Berkeley
- Deep Learning, Stanford University
- MOOC - Neural Networks for Machine Learning, Geoffrey Hinton 2016 - Coursera
- Stat 946 Deep Learning - University of Waterloo
- EECS 298 Theory of Computational Neural Networks and Machine Learning (Fall 2020) - UC Irvine (YouTube)
- ECE 1508 Applied Deep Learning - University of Toronto (Fall 2025) (Winter 2025) (Fall 2024)
- ECE 1508 Reinforcement Learning - Fall 2025 - University of Toronto
- Neural networks class - Université de Sherbrooke (YouTube)
- DLCV - Deep Learning for Computer Vision - UPC Barcelona
- DLAI - Deep Learning for Artificial Intelligence @ UPC Barcelona
- Neural Networks and Applications - IIT Kharagpur
- UVA DEEP LEARNING COURSE
- Deep Learning - Winter 2020-21 - Tübingen Machine Learning
- Geometric Deep Learning - AMMI
- Math for Deep Learning — Andreas Geiger
- Applied Deep Learning 2025 - TU Wien (2024) (2023) (2022) (2021) (2020)
- Neural Networks: Zero to Hero - Andrej Karpathy
- CIS 522 - Deep Learning - U Penn
- UVA DEEP LEARNING COURSE
- Deep Learning (Fall 2020) - FAU (Spring 2020) (Fall 2019) (Spring 2019) (Fall 2018) (Spring 2018)
- Deep Learning (Fall 2020) - Georgia Tech
- Mathematics of Deep Learning (2021) - FAU
- CS7015 - Deep Learning - Prof. Mitesh M. Khapra - IIT Madras
- ETH Zürich | Deep Learning in Scientific Computing 2023
- Deep Learning François Fleuret
- Applied Deep Learning Maziar Raissi
- UC Berkeley CS 182 / 282a Deep Learning spring 2023, by Anant Sahai
- CMSC 828W Foundations of Deep Learning (Fall 2020) - UMD (YouTube)
- TUM IN2346 Introduction to Deep Learning Fall 2024, by Daniel Cremers (Summer 2023)
- UT Austin - Advances in Deep Learning
- HKU - Data 8014 Principles of Deep Representation Learning Fall 2025, by Yi Ma
Reinforcement Learning
- CS234: Reinforcement Learning - Spring 2024 - Stanford University (Winter 2019)
- CSE 542: Reinforcement Learning - Spring 2024 - University of Washington
- CSE 579: Reinforcement Learning - Autumn 2024 - University of Washington
- CSC 2547: Introduction to Reinforcement Learning - Spring 2021 - University of Toronto (YouTube)
- Introduction to reinforcement learning - UCL
- Reinforcement Learning - IIT Madras (TA - Manav Mishra, TA - Prabhleen Kukreja, TA - Sandarbh Yadav , TA - Avik Kar)
- Special topics in ML (Reinforcement Learning) IIT madras
- CS885 Reinforcement Learning - Spring 2018 - University of Waterloo
- CS 224R - Deep Reinforcement Learning- Stanford (YouTube)
- CS 285 - Deep Reinforcement Learning- UC Berkeley
- CS 294 112 - Reinforcement Learning
- NUS CS 6101 - Deep Reinforcement Learning
- ECE 8851: Reinforcement Learning
- CS294-112, Deep Reinforcement Learning Sp17 (YouTube)
- UCL Course 2015 on Reinforcement Learning by David Silver from DeepMind (YouTube)
- Deep RL Bootcamp - Berkeley Aug 2017
- Reinforcement Learning - IIT Madras
- Reinforcement Learning Course at KTH (FDD3359 - 2022)
- Reinforcement Learning Course at ASU, Spring 2022
- CS 4789/5789: Introduction to Reinforcement Learning - Cornell
- S20/IE613 - Online (Machine) Learning/ Bandit Algorithms
- Reinforcement Learning - Fall 2021 chandar-lab
- CMU 10 703 Deep Reinforcement Learning & Control fall 2022, by Katerina Fragkiadaki
- ECE524 Foundations of Reinforcement Learning at Princeton University, Spring 2024
- REINFORCEMENT LEARNING AND OPTIMAL CONTROL - Dimitri P. Bertsekas, ASU
- CMU 16 745 Optimal Control and Reinforcement Learning spring by Zac Manchester
- CMU 16 899 Adaptive Control and Reinforcement Learning fall 2020, by Changliu Liu
- Jadavpur University, 2025: Introduction to Reinforcement Learning
- EE675 (2024) Introduction to Reinforcement Learning Course | IIT Kanpur
- Reinforcement Learning Course by Frédéric Godin - Concordia University
- CS 285: Deep RL, 2023
- Mathematical Foundations of Reinforcement Learning - WINDY Lab
- Reinforcement Learning (HMC CS 181V)—Spring, 2020 - Neil Rhodes
- Reinforcement Learning Course: Lectures (Summer 2023) by Paderborn University
- CS292F (Spring 2021) Statistical Foundation of Reinforcement Learning - UCSD
- Algorithmic Foundations of Interactive Learning - CMU
Advanced Machine Learning
- Advanced Machine Learning, 2021-2022, Sem I - by Prof. Madhavan Mukund, CMI
- 18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT
- CS 330 - Deep Multi-Task and Meta Learning - Fall 2019 - Stanford University (Youtube)
- Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022
- ES 661 (2023): Probabilistic Machine Learning - IIT Gandhinagar
- Information Retrieval in High Dimensional Data
- Trustworthy Machine Learning - Winter Semester 2023-2024, University of Tübingen
- Trustworthy Machine Learning - Winter Semester 2024-2025, University of Tübingen
- ETH Zürich Advanced Machine Learning fall 2019, by Joachim M. Buhmann
- CS 159 Advanced Topics in Machine Learning, Spring 2021 - Caltech
- CS 229br Advanced Topics in the theory of machine learning, Spring 2021 - Harvard
Natural Language Processing
- CS 224N -Natural Language Processing with Deep Learning - Stanford University (Lectures - Winter 2019) (Lectures - Winter 2021) (Lectures - Spring 2024)
- CS 224N - Natural Language Processing, Stanford University (Lecture videos)
- Stanford XCS224U: Natural Language Understanding I Spring 2023
- CS388: Natural Language Processing - UT Austin
- CS 124 - From Languages to Information - Stanford University
- CS 6340/5340 - Natural Language Processing - University of Utah - Spring 2024 (Youtube)
- CSE 447/517 - Natural Language Processing - University of Washington - Winter 2024
- Neural Networks: Zero to Hero - Andrej Karpathy
- fast.ai Code-First Intro to Natural Language Processing (Github)
- MOOC - Natural Language Processing - Coursera, University of Michigan
- Natural Language Processing at UT Austin (Greg Durrett)
- CS224U: Natural Language Understanding - Spring 2019 - Stanford University
- Deep Learning for Natural Language Processing, 2017 - Oxford University
- Natural Language Processing - IIT Bombay
- CMU Advanced NLP Fall 2024 (Lectures - Fall 2024) (Lectures - Fall 2021)
- CMU Neural Nets for NLP 2021
- Natural Language Processing - Michael Collins - Columbia University
- CMU CS11-711 - Advanced Natural Language Processing (Lectures - Spring 2025)
- CMU CS11-737 - Multilingual Natural Language Processing
- UMass CS685: Advanced Natural Language Processing (Spring 2022)
- Natural Language Processing (CMSC 470)
- Stanford CS25 - Transformers United 2023
- Natural Language Processing (IN2361) - TUM
- Natural Language Processing (Spring 2024) - University of Utah
- Multilingual NLP 2020 - CMU
- Speech Technology - IIT Madras
Generative AI and LLMs
- Stanford CS236: Deep Generative Models I 2023 I Stefano Ermon
- CS 6785 - Deep Generative Models - Cornell Tech, Spring 2023)
- ECE 498 / 598 - Deep Generative Models - UIUC, Fall 2025)
- Mathematical Foundations of Generative AI - IIT Madras
- Deep Generative Models - IISC
- A Course on Generative AI - Diffusion Models - Israel Institute of Technology
- MIT 6.S184 Flow Matching and Diffusion Models, 2025
- Course on Diffusion Models for Generative AI - UT Austin
- CS 492(C) Diffusion and Flow Models - Fall 2025 - KAIST (YouTube)
- Stanford CS336 Language Modeling from Scratch I 2025 - Stanford
- Stanford CME295 Transformers & LLMs - Autumn 2025 - Stanford
- Introduction to large language models - IIT Madras
- Build a Large Language Model (From Scratch) by Sebastian Raschka
- Reinforcement Learning of Large Language Models - UCLA
- WING NUS CS6101 Large Language Models (T2310)
- CS 839: Foundation Models Fall 2025 - UW Madison (YouTube playlists)
- CS 886: Recent Advances on Foundation Models Winter 2024 - University of Waterloo
- UC Berkeley CS 194/294-196 Large Language Model Agents Fall 2024, by Dawn Song & Xinyun Chen (YouTube playlist)
- UC Berkeley CS 194/294-267 Understanding Large Language Models Foundations and Safety spring 2024, by Dawn Song & Dan Hendrycks
- Introduction to Large Language Models (LLMs), IIT Delhi
Computer Vision
- CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University
- CS 198-126: Modern Computer Vision Fall 2022 (UC Berkeley)
- Machine Learning for Robotics and Computer Vision, WS 2013/2014 - TU München (YouTube)
- COGSCI 1 - Intro to Cognitive Science Summer 2022 - UC Berkeley
- Informatics 1 - Cognitive Science 2015/16- University of Edinburgh
- Informatics 2A - Processing Formal and Natural Languages 2016-17 - University of Edinburgh
- NOC:Deep Learning For Visual Computing - IIT Kharagpur
- Extreme Classification
- EECS 498/598 - Deep Learning for Computer Vision - University of Michigan - Fall 2019 (Youtube)
- Computer Vision - FAU Spring 2021 (Spring 2018)
- CAP5415 Computer Vision - UCF Fall 2023
- CAP6412 Advanced Computer Vision - UCF Spring 2024 (Youtube)
- CU Boulder CSCI 5722 Computer Vision - CU Boulder Spring 2025 (Youtube)
- Advanced Deep Learning for Computer vision (ADL4CV) (IN2364) - TU Munich (Youtube)
- Advanced Deep Learning for Physics (ADL4P) - TU Munich
- Computer Vision III: Detection, Segmentation and Tracking (CV3DST) (IN2375) - TU Munich
Time Series Analysis
Optimization
- Optimisation for Machine Learning: Theory and Implementation (Hindi) - IIT
- Rochester DSCC 435 Optimization for Machine Learning fall 2023, by Jiaming Liang
- Princeton ELE539/COS512 Optimization for Machine Learning spring 2021, by Chi Jin
- UT Dallas CS 7301 Advanced Topics in Optimization for Machine Learning spring 2021, by Rishabh Iyer (YouTube)
- Convex Analysis, Summer 2021 - TU Braunschweig (YouTube)
- EE364a: Convex Optimization I - Stanford University
- 10-725 Convex Optimization, Spring 2015 - CMU
- 10-725 Convex Optimization: Fall 2016 - CMU
- 10-725 Optimization Fall 2012 - CMU
- 10-801 Advanced Optimization and Randomized Methods - CMU (YouTube)
- [AM 207 - Stochastic Methods for Data Analysis, Inference and Optimization, Harvard University](http://am207.github.io/
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