Introduction
- Please check NOTES for general information about this list.
- Please refer CONTRIBUTING.md for contribution guidelines.
- Introduction to Computer Science
- Data Structures and Algorithms
- Systems Programming
- Database Systems
- Software Engineering
- Artificial Intelligence
- Machine Learning
- Web Programming and Internet Technologies
- Computer Networks
- Math for Computer Scientist
- Theoretical CS and Programming Languages
- Embedded Systems
- Computer Organization and Architecture
- Security
- Computer Graphics
- Image Processing and Computer Vision
- Computational Biology
- Quantum Computing
- Robotics
- Computational Finance
- Misc
- 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
- CS 50 - Introduction to Computer Science, Harvard University (cs50.tv)
- 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 106X - Programming Abstractions in C++ (Lecture Videos)
- CS 107 - Programming Paradigms, Stanford University
- CmSc 150 - Introduction to Programming with Arcade Games, Simpson College
- 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
- 6.006 - Introduction to Algorithms, MIT OCW
- 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
- 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 170 Algorithms - UCBerkeley Fall 2018, Youtube Fall 2018,Bilibili 2013 Bilibili
- ECS 122A - Algorithm Design and Analysis, UC Davis
- 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)
- Informatics 2B - Algorithms, Data Structures and Learning- University of Edinburgh
- 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
- 6.033 Computer System Engineering - MIT
- CS24 Introduction to Computing Systems - California Institute of Technology (Spring 15 version)
- 15-213 Introduction to Computer Systems, Fall 2015 - CMU
- CS361 - COMPUTER SYSTEMS - UIC
- CS 4400 – Computer Systems Fall 2016 - UoUtah
- Systems - Aduni
- CS110: Principles of Computer Systems - Stanford
- Operating Systems
- CS124 Operating Systems - California Institute of Technology, Fall 2018 - Youtube
- CS 162 Operating Systems and Systems Programming, Spring 2015 - University of California, Berkeley
- 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
- 6.828 - Operating System Engineering [Fall 2014]
- 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
- Distributed Systems
- CS 677 - Distributed Operating Systems, Spring 16 - 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 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
- 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 Colloquim on Computer Systems - Stanford University (Lecture videos)
- 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-2018, YouTube-2017, YouTube-2019)
- 15-721 - Database Systems, CMU (YouTube-2017, YouTube-2016)
- 15-721 Advanced Database Systems (Spring 2019) - CMU
- CS122 - Relational Database System Implementation, Winter 2014-2015 - Caltech
- CS 186 - Database Systems, UC Berkeley, Spring 2015 (Lectures- InfoCoBuild)
- 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
- 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
- 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
- Software Testing - IIT Kharagpur
- Informatics 2C - Software Engineering 2014/15- University of Edinburgh
- 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
- 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
- CS 188 - Introduction to Artificial Intelligence, UC Berkeley - Spring 2015
- 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 - 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
- Introduction to Machine Learning
- MOOC Machine Learning Andrew Ng - Coursera/Stanford (Notes)
- Introduction to Machine Learning for Coders
- MOOC - Statistical Learning, Stanford University
- Foundations of Machine Learning Boot Camp, Berkeley Simons Institute
- CS155 - Machine Learning & Data Mining, 2017 - Caltech (Notes) (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)
- 10 - 301/601 - Introduction to Machine Learning - Spring 2020 - CMU
- CMS 165 Foundations of Machine Learning and Statistical Inference - 2020 - Caltech
- Microsoft Research - Machine Learning Course
- CS 446 - Machine Learning, Spring 2019, UIUC( Fall 2016 Lectures)
- 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
- 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, Fall 2016, University of Utah
- 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
- 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
- Python and machine learning - Stanford Crowd Course Initiative
- MOOC - Machine Learning Part 1a - Udacity/Georgia Tech (Part 1b Part 2 Part 3)
- Machine Learning and Pattern Recognition 2015/16- University of Edinburgh
- Introductory Applied Machine Learning 2015/16- University of Edinburgh
- 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
- 10715 Advanced Introduction to Machine Learning
- Introduction to Machine Learning - Spring 2018 - ETH Zurich
- Machine Learning - Pedro Domingos- University of Washington
- Advanced Machine Learning - 2019 - ETH Zürich
- 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
- Data Mining
- CSEP 546, Data Mining - Pedro Domingos, Sp 2016 - University of Washington (YouTube)
- CS 5140/6140 - Data Mining, Spring 2016, University of Utah (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)
- Data Mining: Learning From Large Datasets - Fall 2017 - ETH Zurich
- Information Retrieval - Spring 2018 - ETH Zurich
- CAP6673 - Data Mining and Machine Learning - FAU(Video lectures)
- Data Warehousing and Data Mining Techniques - Technische Universität Braunschweig, Germany
- Data Science
- Data 8: The Foundations of Data Science - UC Berkeley (Summer 17)
- 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 - Summer 19- UC Berkeley
- Distributed Data Analytics (WT 2017/18) - HPI University of Potsdam
- Statistics 133 - Concepts in Computing with Data, Fall 2013 - UC Berkeley
- Data Profiling and Data Cleansing (WS 2014/15) - HPI University of Potsdam
- AM 207 - Stochastic Methods for Data Analysis, Inference and Optimization, Harvard University
- CS 229r - Algorithms for Big Data, Harvard University (Youtube)
- Algorithms for Big Data - IIT Madras
- Probabilistic Graphical Modeling
- MOOC - Probabilistic Graphical Models - Coursera
- CS 6190 - Probabilistic Modeling, Spring 2016, University of Utah
- 10-708 - Probabilistic Graphical Models, Carnegie Mellon University
- Probabilistic Graphical Models, Daphne Koller, Stanford University
- Probabilistic Models - UNIVERSITY OF HELSINKI
- Probabilistic Modelling and Reasoning 2015/16- University of Edinburgh
- Probabilistic Graphical Models, Spring 2018 - Notre Dame
- Deep Learning
- 6.S191: Introduction to Deep Learning - MIT
- Deep Learning CMU
- 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
- 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
- STAT-157 Deep Learning 2019 - UC Berkeley
- Full Stack DL Bootcamp 2019 - UC Berkeley
- Deep Learning, Stanford University
- MOOC - Neural Networks for Machine Learning, Geoffrey Hinton 2016 - Coursera
- Deep Unsupervised Learning -- Berkeley Spring 2020
- Stat 946 Deep Learning - University of Waterloo
- Neural networks class - Université de Sherbrooke (YouTube)
- CS294-158 Deep Unsupervised Learning SP19
- 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
- Nvidia Machine Learning Class
- Deep Learning - Winter 2020-21 - Tübingen Machine Learning
- Reinforcement Learning
- CS234: Reinforcement Learning - Winter 2019 - Stanford University
- Introduction to reinforcement learning - UCL
- Advanced Deep Learning & Reinforcement Learning - UCL
- Reinforcement Learning - IIT Madras
- CS885 Reinforcement Learning - Spring 2018 - University of Waterloo
- 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
- Advanced Machine Learning
- 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
- 18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT
- CS 330 - Deep Multi-Task and Meta Learning - Fall 2019 - Stanford University (Youtube)
- ML based Natural Language Processing and Computer Vision
- CS 224d - Deep Learning for Natural Language Processing, Stanford University (Lectures - Youtube)
- CS 224N - Natural Language Processing, Stanford University (Lecture videos)
- CS 124 - From Languages to Information - Stanford University
- MOOC - Natural Language Processing, Dan Jurafsky & Chris Manning - Coursera
- fast.ai Code-First Intro to Natural Language Processing (Github)
- MOOC - Natural Language Processing - Coursera, University of Michigan
- CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University
- CS224U: Natural Language Understanding - Spring 2019 - Stanford University
- Deep Learning for Natural Language Processing, 2017 - Oxford University
- Machine Learning for Robotics and Computer Vision, WS 2013/2014 - TU München (YouTube)
- Informatics 1 - Cognitive Science 2015/16- University of Edinburgh
- Informatics 2A - Processing Formal and Natural Languages 2016-17 - University of Edinburgh
- Computational Cognitive Science 2015/16- University of Edinburgh
- Accelerated Natural Language Processing 2015/16- University of Edinburgh
- Natural Language Processing - IIT Bombay
- NOC:Deep Learning For Visual Computing - IIT Kharagpur
- CS 11-747 - Neural Nets for NLP - 2019 - CMU
- Natural Language Processing - Michael Collins - Columbia University
- Deep Learning for Computer Vision - University of Michigan
- CMU CS11-737 - Multilingual Natural Language Processing
- Time Series Analysis
- Misc Machine Learning Topics
- EE364a: Convex Optimization I - Stanford University
- CS 6955 - Clustering, Spring 2015, University of Utah
- Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information (YouTube)
- 10-725 Convex Optimization, Spring 2015 - CMU
- 10-725 Convex Optimization: Fall 2016 - CMU
- CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas
- 9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT
- Reinforcement Learning - UCL
- Regularization Methods for Machine Learning 2016 (YouTube)
- Statistical Inference in Big Data - University of Toronto
- 10-725 Optimization Fall 2012 - CMU
- 10-801 Advanced Optimization and Randomized Methods - CMU (YouTube)
- Reinforcement Learning 2015/16- University of Edinburgh
- Reinforcement Learning - IIT Madras
- Statistical Rethinking Winter 2015 - Richard McElreath
- Music Information Retrieval - University of Victoria, 2014
- PURDUE Machine Learning Summer School 2011
- Foundations of Machine Learning - Blmmoberg Edu
- Introduction to reinforcement learning - UCL
- Advanced Deep Learning & Reinforcement Learning - UCL
- Web Information Retrieval (Proff. L. Becchetti - A. Vitaletti)
- Big Data Systems (WT 2019/20) - Prof. Dr. Tilmann Rabl - HPI
- Distributed Data Analytics (WT 2017/18) - Dr. Thorsten Papenbrock - HPI
- 14-740 - Fundamentals of Computer Networks - CMU
- CS 144 Introduction to Computer Networking - Stanford University, Fall 2013 (Lecture videos)
- Computer Communication Networks, Rensselaer Polytechnic Institute - Fall 2001 (Videos) (Slides)
- Audio/Video Recordings and Podcasts of Professor Raj Jain's Lectures - Washington University in St. Louis (YouTube)
- Computer Networks, Tanenbaum, Wetherall Computer Networks 5e - Video Lectures
- CSEP 561 - PMP Network Systems, Fall 2013 - University of Washington (Videos)
- CSEP 561 – Network Systems, Autumn 2008 - University of Washington (Videos)
- Computer Networks - IIT Kharagpur
- Introduction to Data Communications 2013, Steven Gordon - Thammasat University, Thailand
- Introduction to Complex Networks - RIT
- Structural Analysis and Visualization of Networks
- Data Communication - IIT Kharagpur
- Error Correcting Codes - IISC Bangalore
- Information Theory and Coding - IIT Bombay
- Complex Network : Theory and Application - IIT Kharagpur
- Advanced 3G and 4G Wireless Mobile Communications - IIT Kanpur
- Broadband Networks: Concepts and Technology - IIT Bombay
- Coding Theory - IIT Madras
- Digital Communication - IIT Bombay
- Digital Voice & Picture Communication - IIT Kharagpur
- Wireless Ad Hoc and Sensor Networks - IIT Kharagpur
- Internetworking with TCP/IP by Prof. Dr. Christoph Meinel - HPI
- CS798: Mathematical Foundations of Computer Networking - University of Waterloo
- List of Science & Math courses with video lectures
- Calculus
- Discrete Math
- 6.042J - Mathematics for Computer Science, Fall 2010, MIT OCW (Spring 15)
- Computer Science 70, 001 - Spring 2015
- CSE 547 Discrete Mathematics, Prof Skiena, University of Stony Brook
- Discrete Structures (Summer 2011) - Rutgers, The State University of New Jersey
- Discrete Mathematics and Mathematical Reasoning 2015/16 - University of Edinburgh
- Discrete Mathematical Structures - IIT Madras
- Discrete Structures - Pepperdine University
- Probability & Statistics
- 6.041 Probabilistic Systems Analysis and Applied Probability - MIT OCW
- Statistics 110 - Probability - Harvard University
- STAT 2.1x: Descriptive Statistics | UC Berkeley
- STAT 2.2x: Probability | UC Berkeley
- MOOC - Statistics: Making Sense of Data, Coursera
- MOOC - Statistics One - Coursera
- Probability and Random Processes - IIT Kharagpur
- MOOC - Statistical Inference - Coursera
- 131B - Introduction to Probability and Statistics, UCI
- STATS 250 - Introduction to Statistics and Data Analysis, UMichigan
- Sets, Counting and Probability - Harvard
- Opinionated Lessons in Statistics (Youtube)
- Statistics - Brandon Foltz
- Statistical Rethinking: A Bayesian Course Using R and Stan (Lectures - Aalto University) (Book)
- 02402 Introduction to Statistics E12 - Technical University of Denmark (F17)
- Linear Algebra
- 18.06 - Linear Algebra, Prof. Gilbert Strang, MIT OCW
- 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning - MIT OCW
- Linear Algebra (Princeton University)
- MOOC: Coding the Matrix: Linear Algebra through Computer Science Applications - Coursera
- CS 053 - Coding the Matrix - Brown University (Fall 14 videos)
- Linear Algebra Review - CMU
- A first course in Linear Algebra - N J Wildberger - UNSW
- INTRODUCTION TO MATRIX ALGEBRA
- Computational Linear Algebra - fast.ai (Github)
- 10-600 Math Background for ML - CMU
- MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
- 36-705 - Intermediate Statistics - Larry Wasserman, CMU (YouTube)
- Combinatorics - IISC Bangalore
- Advanced Engineering Mathematics - Notre Dame
- Statistical Computing for Scientists and Engineers - Notre Dame
- Statistical Computing, Fall 2017 - Notre Dame
- Mathematics for Machine Learning, Lectures by Ulrike von Luxburg - Tübingen Machine Learning
- Web Design Decal - HTML/CSS/JavaScript Course, University of California, Berkeley
- CS 75 Building Dynamic Websites - Harvard University
- Internet Technology - IIT Kharagpur
- Introduction to Modern Application Development - IIT Madras
- CSE 199 - How the Internet Works, Fall 2016 - University of Buffalo
- Open Sourced Elective: Database and Rails - Intro to Ruby on Rails, University of Texas (Lectures - Youtube)
- CSEP545 - Transaction Processing for E-Commerce, Winter 2012 - University of Washington (Videos)
- CT 310 Web Development - Colorado State University
- Internet Technologies and Applications 2012, Steven Gordon - Thammasat University, Thailand
- CSCI 3110 Advanced Topics in Web Development, Fall 2011 - ETSU iTunes
- CSCI 5710 e-Commerce Implementation, Fall 2015 - ETSU iTunes
- MOOC - Web Development - Udacity
- Web Technologies Prof. Dr. Christoph Meinel - HPI
- MOOC - Compilers - Stanford University
- CS 164 Hack your language, UC Berkeley (Lectures - Youtube)
- Theory of computation - Shai Simonson
- CS 173 Programming Languages, Brown University (Book)
- CS 421 - Programming Languages and Compilers, UIUC
- CSC 253 - CPython internals: A ten-hour codewalk through the Python interpreter source code, University of Rochester
- CSE341 - Programming Languages, Dan Grossman, Spring 2013 - University of Washington
- CSEP 501 - Compiler Construction, University of Washington (Lectures - Youtube)
- CSEP 505 Programming Languages, Winter 2015 - University of Washington
- 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)
- MOOC - Automata - Jeffrey Ullman - Coursera
- CS581 Theory of Computation - Portland State University (Lectures - Youtube)
- Theory of Computation - Fall 2011 UC Davis
- TDA555 Introduction to Functional Programming - Chalmers University of Technology (Lectures - YouTube)
- Philip Wadler Haskell lecture recordings
- Functional Programming - University of Edinburgh - 2016-17
- MOOC - Functional Programming Principles in Scala by Martin Odersky
- CS294 - Program Synthesis for Everyone
- MOOC - Principles of Reactive Programming, Scala - Coursera
- Category Theory for Programmers, 2014 - Bartosz Milewski (YouTube)
- Oregon Programming Languages Summer School (Proof theory, type theory, category theory, verification)
- Inf1 - Computation and Logic 2015 - University of Edinburgh
- INFORMATICS 1 - FUNCTIONAL PROGRAMMING - University of Edinburgh (Videos)
- Compiler Design - IISC Bangalore
- Compiler Design - IIT Kanpur
- Principles of Programming Languages - IIT Delhi
- Principles of Compiler Design - IISC Bangalore
- Functional Programming in Haskell - IIT Madras
- Theory of Computation - IIT Kanpur
- Theory of Automata, Formal Languages and Computation - IIT Madras
- Theory of Computation - IIT Kanpur
- Logic for CS - IIT Delhi
- Principles of Compiler Design - Swarthmore College
- Undergrad Complexity Theory at CMU
- Graduate Complexity Theory at CMU
- Great Ideas in Theoretical Computer Science at CMU
- Analysis of Boolean Functions at CMU
- Theoretical Computer Science (Bridging Course)(Tutorial) - SS 2015
- EE319K Embedded Systems - UT Austin
- EE445L Embedded Systems Design Lab, Fall 2015, UTexas
- CS149 Embedded Systems - Fall 2014 - UCBerkeley
- ECE 4760 Designing with Microcontrollers Fall 2016, Cornell University (Lectures - Youtube)
- ECE 5760 - Advanced Microcontroller Design and system-on-chip, Spring 2016 - Cornell University
- CSE 438/598 Embedded Systems Programming ASU
- Summer Short Course on Embedded Systems Programming
- Internet of Things by Prof. Dr.-Ing. Dietmar P. F. Möller
- CSE 351 - The Hardware/Software Interface, Spring 16 - University of Washington (Coursera)
- ECE 5030 - Electronic Bioinstrumentation, Spring 2014 - Cornell University
- ECE/CS 5780/6780 - Embedded Systems Design, Spring 14 - University of Utah
- Embedded Systems Class - Version 1 - 2011 - UNCC
- Embedded Systems using the Renesas RX63N Processor - Version 3 - UNCC
- ELEC2142 - Embedded Systems Design - UNSW
- Software Engineering for Embedded Systems (WS 2011/12) - HPI Univesrity of Potsdam
- Embedded Software Testing - IIT Madras
- Embedded Systems - IIT Delhi
- Embedded Systems Design - IIT Kharagpur
- ARM Based Development - IIT Madras
- Software Engineering for Self Adaptive Systems - iTunes - HPI Univesrity of Potsdam
- EE260 Embedded Systems by Robert Paz
- IoT Summer School
- ECSE 421 - Embedded Systems - McGill
- EE402 - Object-oriented Programming with Embedded Systems
- NOC:Advanced IOT Applications - IISc Bangalore
- NOC:Design for internet of things - IISc Bangalore
- Computer Organization
- How Computers Work - Aduni
- CS 61C - Machine Structures, UC Berkeley (Lectures - InfoCoBuild)
- 6.004 - Computation Structures Spring 2013, MIT
- CS/ECE 3810 Computer Organization, Fall 2015, , University of Utah (YouTube)
- Digital Computer Organization - IIT Kharagpur
- Computer Organization - IIT Madras
- CS-224 - Computer Organization, 2009-2010 Spring, Bilkent University (YouTube playlist)
- INFORMATICS 2C - INTRODUCTION TO COMPUTER SYSTEMS (AUTUMN 2016) - University of Edinburgh
- Computer Architecture
- 18-447 - Introduction to Computer Architecture, CMU (Lectures - YouTube - Fall 15)
- CS 152 Computer Architecture and Engineering, UC Berkeley
- CSEP 548 - Computer Architecture Autumn 2012 - University of Washington
- CS/ECE 6810 Computer Architecture, Spring 2016, University of Utah (YouTube)
- MOOC - Computer Architecture, David Wentzlaff - Princeton University/Coursera
- Computer Architecture - ETH Zürich - Fall 2019
- Digital Circuits and Computer Architecture - ETH Zurich - Spring 2017
- Computer Architecture - IIT Delhi
- Computer Architecture - IIT Kanpur
- Computer Architecture - IIT Madras
- High Performance Computer Architecture - IIT Kharagpur
- Parallel Computer Architecture
- 15-418 - Parallel Computer Architecture and Programming, CMU (Lecture Videos)
- CS 267 Applications of Parallel Computers, Spring 16 - UC Berkeley (YouTube)
- MOOC - Heterogeneous Parallel Programming - Coursera
- ECE 498AL - Programming Massively Parallel Processors
- Parallel Computing - IIT Delhi
- Parallel Architectures 2012/13- University of Edinburgh
- Digital Systems Design
- CS1 - Higher Computing - Richard Buckland UNSW
- MOOC - From NAND to TetrisBuilding a Modern Computer From First Principles (YouTube)
- System Validation, TU Delft
- High Performance Computing - IISC Bangalore
- Introduction to ARM - Open SecurityTraining
- Intro x86 (32 bit) - Open SecurityTraining
- Intermediate x86 (32 bit) - Open SecurityTraining
- Design of Digital Circuits - ETH Zürich - Spring 2019
- Onur Mutlu @ TU Wien 2019 - Memory Systems
- Memory Systems Course - Technion, Summer 2018
- Internet Security (WT 2018/19) - HPI University of Potsdam
- 6.858 Computer Systems Security - MIT OCW
- CS 161: Computer Security, UC Berkeley
- 6.875 - Cryptography - Spring 2018- MIT
- CSEP590A - Practical Aspects of Modern Cryptography, Winter 2011 - University of Washington (Videos)
- CS461/ECE422 - Computer Security - University of Illinois at Urbana-Champaign (Videos)
- Introduction to Cryptography, Christof Paar - Ruhr University Bochum, Germany
- ECS235B Foundations of Computer and Information Security - UC Davis
- CIS 4930/ CIS 5930 - Offensive Computer Security, Florida State University
- Introduction to Information Security I - IIT Madras
- Information Security - II - IIT Madras
- Introduction to Cryptology - IIT Roorkee
- Cryptography and Network Security - IIT Kharagpur
- 18-636 Browser Security, Stanford
- Internet Security - Weaknesses and Targets (WT 2015/16) (WT 2012/13 (YouTube))
- IT Security, Steven Gordon - Thammasat University, Thailand
- Security and Cryptography, Steven Gordon - Thammasat University, Thailand
- MOOC - Cryptography - Coursera
- MOOC - Intro to Information Security - Udacity
- ICS 444 - Computer & Network Security
- Privacy and Security in Online Social Networks - IIT Madras
- Malware Dynamic Analysis - Open SecurityTraining (YouTube)
- CSN09112 - Network Security and Cryptography - Bill Buchanan - Edinburgh Napier
- CSN10107 - Security Testing and Network Forensics - Bill Buchanan - Edinburgh Napier
- CSN11123 - Advanced Cloud and Network Forensics - Bill Buchanan - Edinburgh Napier
- CSN11117 - e-Security - Bill Buchanan - Edinburgh Napier
- CSN08704 - Telecommunications - Bill Buchanan - Edinburgh Napier
- CSN11128 - Incident Response and Malware Analysus - Bill Buchanan - Edinburgh Napier
- Internet Security for Beginners by Dr. Christoph Meinel - HPI
- CS184 - Computer Graphics, Fall 2012 - UC Berkeley
- ECS 175 - Computer Graphics, Fall 2009 - UC Davis
- 6.837 - Computer Graphics - Spring 2017 - MIT
- 6.838 - Shape Analysis - Spring 2017- MIT
- Introduction to Computer Graphics - IIT Delhi
- Computer Graphics - IIT Madras
- Computer Graphics 2012, Wolfgang Huerst, Utrecht University
- CS 5630/6630 - Visualization, Fall 2016, University of Utah (Lectures - Youtube)
- Advanced Visualization UC Davis
- CSCI E-234 - Introduction to Computer Graphics and GPU Programming, Harvard Extension School
- Computer Graphics Fall 2011, Barbara Hecker
- Introduction to Graphics Architecture
- Ray Tracing for Global Illumination, UCDavis
- Rendering / Ray Tracing Course, SS 2015 - TU Wien
- ECS 178 Introduction to Geometric Modeling, Fall 2012, UC Davis (iTunes)
- Computational Geometry - IIT Delhi
- CS 468 - Differential Geometry for Computer Science - Stanford University (Lecture videos)
- CMU 15-462/662: Computer Graphics
- MOOC - Digital Image procesing - Duke/Coursera
- Computer Vision 2011 - EPFL, Switzerland
- Digital Image Processing - IIT Kharagpur
- Image Processing and Analysis - UC Davis
- CS 543 - Computer Vision – Spring 2017 (Recordings)
- CAP 5415 - Computer Vision - University of Central Florida(Video Lectures)
- EE225B - Digital Image Processing, Spring 2014 - UC Berkeley (Videos - Spring 2006)
- EE637 - Digital Image Processing I - Purdue University (Videos - Sp 2011 ,Videos - Sp 2007)
- Computer Vision I: Variational Methods - TU München (YouTube)
- Computer Vision II: Multiple View Geometry (IN2228), SS 2016 - TU München (YouTube)
- EGGN 510 - Image and Multidimensional Signal Processing - Colorado School of Mines
- EENG 512/CSCI 512 - Computer Vision - Colorado School of Mines
- Computer Vision for Visual Effects - RPI (YouTube)
- Introduction to Image Processing - RPI (YouTube)
- CAP 6412 - Advanced Computer Vision - University of Central Florida(Video lectures) (Spring 2018)
- Digital Signal Processing - RPI
- Advanced Vision 2014 - University of Edinburgh
- Photogrammetry Course - 2015/16 - University of Bonn, Germany
- MOOC - Introduction to Computer Vision - Udacity
- ECSE-4540 - Intro to Digital Image Processing - Spring 2015 - RPI
- Machine Learning for Computer Vision - Winter 2017-2018 - UniHeidelberg
- High-Level Vision - CBCSL OSU
- Advanced Computer Vision - CBCSL OSU
- Introduction to Image Processing & Computer Vision - CBCSL OSU
- Machine Learning for Computer Vision - TU Munich
- Biometrics - IIT Kanpur
- Quantitative Big Imaging 2019 ETH Zurich
- Multiple View Geometry in Computer Vision
- 3D Coordinate Systems – Remote Course (GE, 2020) - University of Bonn (2013 lectures)
- Modern C++ Course For CV (2020) - University of Bonn
- Photogrammetry 1 Course – 2020 - University of Bonn
- Photogrammetry II Course 2020/21 - University of Bonn
- ECS 124 - Foundations of Algorithms for Bioinformatics - Dan Gusfield, UC Davis (YouTube)
- CSE549 - Computational Biology - Steven Skiena - 2010 SBU
- 7.32 Systems Biology, Fall 2014 - MIT OCW
- 6.802J/ 6.874J Foundations of Computational and Systems Biology - MIT OCW
- 6.047/6.878 Public Lectures on Computational Biology: Genomes, Networks, Evolution - MIT
- Bio 84 - Your Genes and Your Health, Stanford University
- BioMedical Informatics 231 Computational Molecular Biology, Stanford University
- BioMedical Informatics 258 Genomics, Bioinformatics & Medicine, Stanford University
- 03-251: Introduction to Computational Molecular Biology - Carnegie Mellon University
- 03-712: Biological Modeling and Simulation - Carnegie Mellon University
- MOOC - Bioinformatics Algorithms: An Active Learning Approach - UC San Diego/Coursera
- Neural Networks and Biological Modeling - Lecturer: Prof. Wulfram Gerstner - EPFL
- Video Lectures of Wulfram Gerstner: Computational Neuroscience - EPFL
- An Introduction To Systems Biology
- Introduction to Bioinformatics, METUOpenCourseWare
- MOOC - Algorithms for DNA Sequencing, Coursera
- Frontiers of Biomedical Engineering with W. Mark Saltzman - Yale
- NOC:Computational Systems Biology - IIT Madras
- NOC:BioInformatics:Algorithms and Applications - IIT Madras
- 15-859BB: Quantum Computation and Quantum Information 2018 - CMU (Youtube)
- Quantum Mechanics for Scientists and Engineers
- Quantum Mechanics and Quantum Computation - Umesh Vazirani
- Quantum Information and Computing by Prof. D.K. Ghosh
- Quantum Computing by Prof. Debabrata Goswami
- The Building Blocks of a Quantum Computer: Part 1 - TU Delft
- The Building Blocks of a Quantum Computer: Part 2 - TU Delft
- Quantum Cryptography - TU Delft
- CS 223A - Introduction to Robotics, Stanford University
- 6.832 Underactuated Robotics - MIT OCW
- CS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter Abbeel
- CS 287 - Advanced Robotics, Fall 2011, UC Berkeley (Videos)
- CS235 - Applied Robot Design for Non-Robot-Designers - Stanford University
- Lecture: Visual Navigation for Flying Robots (YouTube)
- CS 205A: Mathematical Methods for Robotics, Vision, and Graphics (Fall 2013)
- Robotics 1, Prof. De Luca, Università di Roma (YouTube)
- Robotics 2, Prof. De Luca, Università di Roma (YouTube)
- Robot Mechanics and Control, SNU
- Introduction to Robotics Course - UNCC
- SLAM Lectures
- Introduction to Vision and Robotics 2015/16- University of Edinburgh
- ME 597 – Autonomous Mobile Robotics – Fall 2014
- ME 780 – Perception For Autonomous Driving – Spring 2017
- ME780 – Nonlinear State Estimation for Robotics and Computer Vision – Spring 2017
- METR 4202/7202 -- Robotics & Automation - University of Queensland
- Robotics - IIT Bombay
- Introduction to Machine Vision
- 6.834J Cognitive Robotics - MIT OCW
- Hello (Real) World with ROS – Robot Operating System - TU Delft
- Programming for Robotics (ROS) - ETH Zurich
- Mechatronic System Design - TU Delft
- CS 206 Evolutionary Robotics Course Spring 2020
- Foundations of Robotics - UTEC 2018-I
- Robotics - Youtube
- Robotics and Control: Theory and Practice IIT Roorkee
- Mechatronics
- ME142 - Mechatronics Spring 2020 - UC Merced
- Mobile Sensing and Robotics - Bonn University
- MSR2 - Sensors and State Estimation Course (2020) - Bonn University
- SLAM Course (2013) - Bonn University
- ENGR486 Robot Modeling and Control (2014W)
- Robotics by Prof. D K Pratihar - IIT Kharagpur
- Introduction to Mobile Robotics - SS 2019 - Universität Freiburg
- Robot Mapping - WS 2018/19 - Universität Freiburg
- Mechanism and Robot Kinematics - IIT Kharagpur
- Self-Driving Cars - Cyrill Stachniss - Winter 2020/21 - University of Bonn)
- Mobile Sensing and Robotics 1 – Part Stachniss (Jointly taught with PhoRS) - University of Bonn
- Mobile Sensing and Robotics 2 – Stachniss & Klingbeil/Holst - University of Bonn
- COMP510 - Computational Finance - Steven Skiena - 2007 HKUST
- MOOC - Mathematical Methods for Quantitative Finance, University of Washington/Coursera)
- 18.S096 Topics in Mathematics with Applications in Finance, MIT OCW
- Computational Finance - Universität Leipzig
- Machine Learning for Trading | Udacity
- ACT 460 / STA 2502 – Stochastic Methods for Actuarial Science - University of Toronto
- MMF1928H / STA 2503F – Pricing Theory I / Applied Probability for Mathematical Finance - University of Toronto
- STA 4505H – High Frequency & Algorithmic trading - University of Toronto
- Mathematical Finance - IIT Guwahati
- Quantitative Finance - IIT Kanpur
- Financial Derivatives & Risk Management - IIT Roorkee
- Financial Mathematics - IIT Roorkee
- HCI
- Game Development
- Geospatial
- SCICOMP - An Introduction to Efficient Scientific Computation, Universität Bremen
- CS E-259 XML with Java, Java Servlet, and JSP - Harvard
- CSE 40373 - Spr 2009: Multimedia Systems
- Exposing Digital Photography - Harvard Extension School
- MOOC - Matlab - Coursera
- Computing for Computer Scientists - University of Michigan
- Linux Implementation/Administration Practicum - Redhat by Tulio Llosa
- SIMS 141 - Search Engines - Fall 2005 UCBerkeley
- Innovative Computing - Harvard University
- Linux Programming & Scripting - IIT Madras
- Model Checking - IIT Madras
- Virtual Reality - IIT Madras
- CS 195 - Social Implications of Computing, Spring 2015 - UC Berkeley (YouTube)
- Spatial Databases and Geographic Information Systems - Technische Universität Braunschweig, Germany (in German)
- Dependable Systems (SS 2014) - HPI University of Potsdam
- Business Process Compliance (WT 2013/14) - HPI University of Potsdam
- Design Thinking for Digital Engineering (SS 2018) - Dr. Julia von Thienen - HPI
- CS224w – Social Network Analysis – Autumn 2017 - Stanford University
- Blockchain and Cryptocurrencies