- Recently quality of MOOCs has diminished, therefore only MOOCs with comprehensive lecture material which cover a subject/topic in ample detail will be added. For example, MOOC on Computer Networks or Machine Learning with 4-5 hours may not be able to cover all topics in sufficient detail and thus should be avoided.
- One philosophy used in this list while integrating MOOCs is that link should directly point to videos for viewing/downloading than registration and waiting for the next session. If videos are directly accessible through the platform/youtube or any other source, please use the direct source. This is list of video courses, not a list of MOOCs.
- Courses within a section are roughly sorted in terms of level i.e. undergraduate courses followed by upper level undergraduate, followed by graduate courses. As courses are from multiple Universities, sorting is not perfect and only an approximation. For example, while adding a new undergraduate course on Algorithms, please feel free to add it along with other Algorithms courses than after graduate courses.
- Intent of this list is to act as Online bookmarks/lookup table for freely available online video courses. Focus would be to keep the list concise so that it is easy to browse. It would be easier to skim through 15 page list, find the course and start learning than having to read 60 pages of text. If you are student or from non-CS background, please try few courses to decide for yourself as to which course suits your learning curve best.
- 90% courses on Data Structures/Algorithms/Operating Systems/Machine Learning/Computer Networks/etc tend to have 80-90% overlap in curriculum. Descriptions for courses are helpful but adding descriptions/comments for each course can lead to repetition/subjective opinions. As a tradeoff, metadata like course number, name, prof, year, University/platform for Course is added in the URL itself. To access syllabus/notes/assignments, please visit link to the course or use Google search with course number/name. If a course has excellent notes/assignments/projects which cannot be reached through video's link, please feel free to add links alongside.
- If available, please add following information to the link - <Course-Number><Course-Name><Year><Prof Name><University Name/Platform>.
- If you are bored reading above 10 lines, imagine reading descriptions for hundreds of courses :)
- If You need assistance in deciding order in which courses should be taken, please refer to sample Course prerequisite charts by Universities to familiarize yourself with standard CS curriculum. If you need to know prerequisites for a particular course not covered by below samples, please check the course link or try Google.
- If You need assistance in deciding order in which courses should be taken, please refer to sample Course prerequsite charts by Universities to familiarize yourself with standard CS curriculum. If you need to know prerequisites for a particular course not covered by below samples, please check the course link or try Google.
- [Modern C++ Course (2018) - Bonn University](https://www.youtube.com/playlist?list=PLgnQpQtFTOGR50iIOtO36nK6aNPtVq98C)
- [Modern C++ (Lecture & Tutorials, 2020, Vizzo & Stachniss) - University of Bonn](https://www.youtube.com/playlist?list=PLgnQpQtFTOGRM59sr3nSL8BmeMZR9GCIA)
------------------------------
------
### Data Structures and Algorithms
@ -120,7 +118,7 @@ Table of Contents
- [Graph Theory - IISC Bangalore](https://nptel.ac.in/courses/106108054/)
- [In-Memory Data Management (2013)Prof. Hasso Plattner - HPI](https://open.hpi.de/courses/imdb2013/items/72j6pftms3dOSunM98JhfW)
- [Distributed Data Management (WT 2019/20) - Dr. Thorsten Papenbrock - HPI](https://www.tele-task.de/series/1285/)
------------------------------
### Software Engineering
- **Object Oriented Design**
- [ECE 462 Object-Oriented Programming using C++ and Java - Purdue](https://engineering.purdue.edu/OOSD/F2008/F2008.html)
- [Object-oriented Program Design and Software Engineering - Aduni](http://aduni.org/courses/java/index.php?view=cw)
- [OOSE - Object-Oriented Software Engineering, Dr. Tim Lethbridge](https://www.youtube.com/playlist?list=PL6iDJCG2nkhfNlig8NY5ePPfGvtQX6yLa)
- [Object Oriented Systems Analysis and Design (Systems Analysis and Design in a Changing World)](https://www.youtube.com/playlist?list=PL6XklZATqYx9dj72MKG6wLYjljeB2odra)
- [OOSE - Software Dev Using UML and Java](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
- [Object-Oriented Analysis and Design - IIT Kharagpur](https://nptel.ac.in/courses/106105153/)
- [CS3 - Design in Computing - Richard Buckland UNSW](https://www.youtube.com/course?list=EC0C5D85DBA20E685C)
- [Informatics 1 - Object-Oriented Programming 2014/15- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2014/inf1op.htm)
- [Software Engineering with Objects and Components 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/seoc.htm)
- [ECE 462 Object-Oriented Programming using C++ and Java - Purdue](https://engineering.purdue.edu/OOSD/F2008/F2008.html)
- [Object-oriented Program Design and Software Engineering - Aduni](http://aduni.org/courses/java/index.php?view=cw)
- [OOSE - Object-Oriented Software Engineering, Dr. Tim Lethbridge](https://www.youtube.com/playlist?list=PL6iDJCG2nkhfNlig8NY5ePPfGvtQX6yLa)
- [Object Oriented Systems Analysis and Design (Systems Analysis and Design in a Changing World)](https://www.youtube.com/playlist?list=PL6XklZATqYx9dj72MKG6wLYjljeB2odra)
- [Introduction to Service Design and Engineering - University of Trento, Italy](https://www.youtube.com/playlist?list=PLBdajHWwi0JCn87QuFT3e58mekU0-6WUT)
- [Introduction to Service Design and Engineering - University of Trento, Italy](https://www.youtube.com/playlist?list=PLBdajHWwi0JCn87QuFT3e58mekU0-6WUT)
- [CS176 - Multiprocessor Synchronization - Brown University](http://cs.brown.edu/courses/cs176/course_information.shtml) ([Videos from 2012](http://www.brown.edu/cis/sta/dev/herlihy_csci1760_fa12/#vid))
- [CS 282 (2014): Concurrent Java Network Programming in Android](https://www.youtube.com/playlist?list=PLZ9NgFYEMxp4KSJPUyaQCj7x--NQ6kvcX)
- [CSE P 506 – Concurrency, Spring 2011 - University of Washington](https://courses.cs.washington.edu/courses/csep506/11sp/Home.html) ([Videos](https://courses.cs.washington.edu/courses/csep506/11sp/Videos.html))
- [CSEP 524 - Parallel Computation - University of Washington](https://courses.cs.washington.edu/courses/csep524/10sp/) ([Videos](https://courses.cs.washington.edu/courses/csep524/10sp/lectures/video.html))
- [Parallel Programming Concepts (WT 2013/14) - HPI University of Potsdam](https://www.tele-task.de/series/977/)
- [Parallel Programming Concepts (WT 2012/13) - HPI University of Potsdam](https://www.tele-task.de/series/924/)
- [CS176 - Multiprocessor Synchronization - Brown University](http://cs.brown.edu/courses/cs176/course_information.shtml) ([Videos from 2012](http://www.brown.edu/cis/sta/dev/herlihy_csci1760_fa12/#vid))
- [CS 282 (2014): Concurrent Java Network Programming in Android](https://www.youtube.com/playlist?list=PLZ9NgFYEMxp4KSJPUyaQCj7x--NQ6kvcX)
- [CSE P 506 – Concurrency, Spring 2011 - University of Washington](https://courses.cs.washington.edu/courses/csep506/11sp/Home.html) ([Videos](https://courses.cs.washington.edu/courses/csep506/11sp/Videos.html))
- [CSEP 524 - Parallel Computation - University of Washington](https://courses.cs.washington.edu/courses/csep524/10sp/) ([Videos](https://courses.cs.washington.edu/courses/csep524/10sp/lectures/video.html))
- [Parallel Programming Concepts (WT 2013/14) - HPI University of Potsdam](https://www.tele-task.de/series/977/)
- [Parallel Programming Concepts (WT 2012/13) - HPI University of Potsdam](https://www.tele-task.de/series/924/)
- **Mobile Application Development**
- [MOOC Programming Mobile Applications for Android Handheld Systems - University of Maryland](https://www.youtube.com/playlist?list=PLkHsKoi6eZnwilGXUc95CqS7Vw4uLLDLG)
- [CS 193p - Developing Applications for iOS, Stanford University](https://itunes.apple.com/us/course/developing-ios-9-apps-swift/id1104579961)
- [CS S-76 Building Mobile Applications - Harvard](http://cs76.tv/2013/summer/)
- [Mobile Information Systems - Bauhaus-Uni Weimar](https://www.youtube.com/watch?v=8EmbrZJwMOI&list=PLjEglKdMOevWv4zPW0diw7iJFdT7s4sTP)
- [MOOC Programming Mobile Applications for Android Handheld Systems - University of Maryland](https://www.youtube.com/playlist?list=PLkHsKoi6eZnwilGXUc95CqS7Vw4uLLDLG)
- [CS 193p - Developing Applications for iOS, Stanford University](https://itunes.apple.com/us/course/developing-ios-9-apps-swift/id1104579961)
- [CS S-76 Building Mobile Applications - Harvard](http://cs76.tv/2013/summer/)
- [Mobile Information Systems - Bauhaus-Uni Weimar](https://www.youtube.com/watch?v=8EmbrZJwMOI&list=PLjEglKdMOevWv4zPW0diw7iJFdT7s4sTP)
------------------------------
### Artificial Intelligence
- [CS50 - Introduction to Artificial Intelligence with Python (and Machine Learning), Harvard OCW](https://cs50.harvard.edu/ai/2020/)
- [CS 188 - Introduction to Artificial Intelligence, UC Berkeley - Spring 2015](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs188-spring2015-berkeley.html)
- [6.034 Artificial Intelligence, MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/lecture-videos/)
@ -273,196 +273,197 @@ Table of Contents
- [Semantic Web Technologies by Dr. Harald Sack - HPI](https://www.youtube.com/playlist?list=PLoOmvuyo5UAeihlKcWpzVzB51rr014TwD)
- [Knowledge Engineering with Semantic Web Technologies by Dr. Harald Sack - HPI](https://www.youtube.com/playlist?list=PLoOmvuyo5UAcBXlhTti7kzetSsi1PpJGR)
------------------------------
--------------
### Machine Learning
- **Introduction to Machine Learning**
- [MOOC Machine Learning Andrew Ng - Coursera/Stanford](https://www.youtube.com/playlist?list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN) ([Notes](http://www.holehouse.org/mlclass/))
- [Introduction to Machine Learning for Coders](https://course.fast.ai/ml.html)
- [CS 156 - Learning from Data, Caltech](https://work.caltech.edu/lectures.html)
- [10-601 - Introduction to Machine Learning (MS) - Tom Mitchell - 2015, CMU](http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml) ([YouTube](https://www.youtube.com/playlist?list=PLAJ0alZrN8rD63LD0FkzKFiFgkOmEtltQ))
- [10-601 Machine Learning | CMU | Fall 2017](https://www.youtube.com/playlist?list=PL7k0r4t5c10-g7CWCnHfZOAxLaiNinChk)
- [10-701 - Introduction to Machine Learning (PhD) - Tom Mitchell, Spring 2011, CMU](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) ([Fall 2014](https://www.youtube.com/playlist?list=PL7y-1rk2cCsDZCVz2xS7LrExqidHpJM3B)) ([Spring 2015 by Alex Smola](https://www.youtube.com/playlist?list=PLZSO_6-bSqHTTV7w9u7grTXBHMH-mw3qn))
- [10 - 301/601 - Introduction to Machine Learning - Spring 2020 - CMU](https://www.youtube.com/playlist?list=PLpqQKYIU-snAPM89YPPwyQ9xdaiAdoouk)
- [CMS 165 Foundations of Machine Learning and Statistical Inference - 2020 - Caltech](https://www.youtube.com/playlist?list=PLVNifWxslHCDlbyitaLLYBOAEPbmF1AHg)
- [Microsoft Research - Machine Learning Course](https://www.youtube.com/playlist?list=PL34iyE0uXtxo7vPXGFkmm6KbgZQwjf9Kf)
- [10-605 - Machine Learning with Large Datasets, Fall 2016 - CMU](https://www.youtube.com/channel/UCIE4UdPoCJZMAZrTLuq-CPQ/videos)
- [Information Theory, Pattern Recognition, and Neural Networks - University of Cambridge](https://www.youtube.com/playlist?list=PLruBu5BI5n4aFpG32iMbdWoRVAA-Vcso6)
- [Python and machine learning - Stanford Crowd Course Initiative](https://www.youtube.com/playlist?list=PLVxFQjPUB2cnYGZPAGG52OQc9SpWVKjjB)
- [Machine Learning Summer School 2013 - Max Planck Institute for Intelligent Systems Tübingen](https://www.youtube.com/playlist?list=PLqJm7Rc5-EXFv6RXaPZzzlzo93Hl0v91E)
- [Machine Learning - Professor Kogan (Spring 2016) - Rutgers](https://www.youtube.com/playlist?list=PLauepKFT6DK_1_plY78bXMDj-bshv7UsQ)
- [CS273a: Introduction to Machine Learning](http://sli.ics.uci.edu/Classes/2015W-273a) ([YouTube](https://www.youtube.com/playlist?list=PLkWzaBlA7utJMRi89i9FAKMopL0h0LBMk))
- [Probabilistic Machine Learning 2020 - University of Tübingen](https://www.youtube.com/playlist?list=PL05umP7R6ij1tHaOFY96m5uX3J21a6yNd)
- [Statistical Machine Learning 2020 - Ulrike von Luxburg - University of Tübingen](https://www.youtube.com/playlist?list=PL05umP7R6ij2XCvrRzLokX6EoHWaGA2cC)
- [COMS W4995 - Applied Machine Learning - Spring 2020 - Columbia University](https://www.cs.columbia.edu/~amueller/comsw4995s20/schedule/)
- [MOOC Machine Learning Andrew Ng - Coursera/Stanford](https://www.youtube.com/playlist?list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN) ([Notes](http://www.holehouse.org/mlclass/))
- [Introduction to Machine Learning for Coders](https://course.fast.ai/ml.html)
- [CS 156 - Learning from Data, Caltech](https://work.caltech.edu/lectures.html)
- [10-601 - Introduction to Machine Learning (MS) - Tom Mitchell - 2015, CMU](http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml) ([YouTube](https://www.youtube.com/playlist?list=PLAJ0alZrN8rD63LD0FkzKFiFgkOmEtltQ))
- [10-601 Machine Learning | CMU | Fall 2017](https://www.youtube.com/playlist?list=PL7k0r4t5c10-g7CWCnHfZOAxLaiNinChk)
- [10-701 - Introduction to Machine Learning (PhD) - Tom Mitchell, Spring 2011, CMU](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) ([Fall 2014](https://www.youtube.com/playlist?list=PL7y-1rk2cCsDZCVz2xS7LrExqidHpJM3B)) ([Spring 2015 by Alex Smola](https://www.youtube.com/playlist?list=PLZSO_6-bSqHTTV7w9u7grTXBHMH-mw3qn))
- [10 - 301/601 - Introduction to Machine Learning - Spring 2020 - CMU](https://www.youtube.com/playlist?list=PLpqQKYIU-snAPM89YPPwyQ9xdaiAdoouk)
- [CMS 165 Foundations of Machine Learning and Statistical Inference - 2020 - Caltech](https://www.youtube.com/playlist?list=PLVNifWxslHCDlbyitaLLYBOAEPbmF1AHg)
- [Microsoft Research - Machine Learning Course](https://www.youtube.com/playlist?list=PL34iyE0uXtxo7vPXGFkmm6KbgZQwjf9Kf)
- [10-605 - Machine Learning with Large Datasets, Fall 2016 - CMU](https://www.youtube.com/channel/UCIE4UdPoCJZMAZrTLuq-CPQ/videos)
- [Information Theory, Pattern Recognition, and Neural Networks - University of Cambridge](https://www.youtube.com/playlist?list=PLruBu5BI5n4aFpG32iMbdWoRVAA-Vcso6)
- [Python and machine learning - Stanford Crowd Course Initiative](https://www.youtube.com/playlist?list=PLVxFQjPUB2cnYGZPAGG52OQc9SpWVKjjB)
- [Machine Learning Summer School 2013 - Max Planck Institute for Intelligent Systems Tübingen](https://www.youtube.com/playlist?list=PLqJm7Rc5-EXFv6RXaPZzzlzo93Hl0v91E)
- [Machine Learning - Professor Kogan (Spring 2016) - Rutgers](https://www.youtube.com/playlist?list=PLauepKFT6DK_1_plY78bXMDj-bshv7UsQ)
- [CS273a: Introduction to Machine Learning](http://sli.ics.uci.edu/Classes/2015W-273a) ([YouTube](https://www.youtube.com/playlist?list=PLkWzaBlA7utJMRi89i9FAKMopL0h0LBMk))
- [Probabilistic Machine Learning 2020 - University of Tübingen](https://www.youtube.com/playlist?list=PL05umP7R6ij1tHaOFY96m5uX3J21a6yNd)
- [Statistical Machine Learning 2020 - Ulrike von Luxburg - University of Tübingen](https://www.youtube.com/playlist?list=PL05umP7R6ij2XCvrRzLokX6EoHWaGA2cC)
- [COMS W4995 - Applied Machine Learning - Spring 2020 - Columbia University](https://www.cs.columbia.edu/~amueller/comsw4995s20/schedule/)
- **Data Mining**
- [CSEP 546, Data Mining - Pedro Domingos, Sp 2016 - University of Washington](https://courses.cs.washington.edu/courses/csep546/16sp/) ([YouTube](https://www.youtube.com/playlist?list=PLTPQEx-31JXgtDaC6-3HxWcp7fq4N8YGr))
- [CS 5140/6140 - Data Mining, Spring 2016, University of Utah](https://www.cs.utah.edu/~jeffp/teaching/cs5140.html) ([Youtube](https://www.youtube.com/playlist?list=PLbuogVdPnkCpXfb43Wvc7s5fXWzedwTPB))
- [CS 5955/6955 - Data Mining, University of Utah](http://www.cs.utah.edu/~jeffp/teaching/cs5955.html) ([YouTube](https://www.youtube.com/channel/UCcrlwW88yMcXujhGjSP2WBg/videos))
- [Statistics 202 - Statistical Aspects of Data Mining, Summer 2007 - Google](http://www.stats202.com/original_index.html) ([YouTube](https://www.youtube.com/playlist?list=PLFE776F2C513A744E))
- [MOOC - Text Mining and Analytics by ChengXiang Zhai](https://www.youtube.com/playlist?list=PLLssT5z_DsK8Xwnh_0bjN4KNT81bekvtt)
- [Information Retrieval SS 2014, iTunes - HPI](https://itunes.apple.com/us/itunes-u/information-retrieval-ss-2014/id874200291)
- [MOOC - Data Mining with Weka](https://www.youtube.com/playlist?list=PLm4W7_iX_v4NqPUjceOGd-OKNVO4c_cPD)
- [Data Mining: Learning From Large Datasets - Fall 2017 - ETH Zurich](https://www.youtube.com/playlist?list=PLY-OA_xnxFwRHZO6L6yT253VPgrZazQs6)
- [Information Retrieval - Spring 2018 - ETH Zurich](https://www.youtube.com/playlist?list=PLzn6LN6WhlN1ktkDvNurPSDwTQ_oGQisn)
- [CAP6673 - Data Mining and Machine Learning - FAU](http://www.cse.fau.edu/~taghi/classes/cap6673/)([Video lectures](https://vimeo.com/album/1505953))
- [Data Warehousing and Data Mining Techniques - Technische Universität Braunschweig, Germany](http://www.ifis.cs.tu-bs.de/teaching/ws-1617/dwh)
- [CSEP 546, Data Mining - Pedro Domingos, Sp 2016 - University of Washington](https://courses.cs.washington.edu/courses/csep546/16sp/) ([YouTube](https://www.youtube.com/playlist?list=PLTPQEx-31JXgtDaC6-3HxWcp7fq4N8YGr))
- [CS 5140/6140 - Data Mining, Spring 2016, University of Utah](https://www.cs.utah.edu/~jeffp/teaching/cs5140.html) ([Youtube](https://www.youtube.com/playlist?list=PLbuogVdPnkCpXfb43Wvc7s5fXWzedwTPB))
- [CS 5955/6955 - Data Mining, University of Utah](http://www.cs.utah.edu/~jeffp/teaching/cs5955.html) ([YouTube](https://www.youtube.com/channel/UCcrlwW88yMcXujhGjSP2WBg/videos))
- [Statistics 202 - Statistical Aspects of Data Mining, Summer 2007 - Google](http://www.stats202.com/original_index.html) ([YouTube](https://www.youtube.com/playlist?list=PLFE776F2C513A744E))
- [MOOC - Text Mining and Analytics by ChengXiang Zhai](https://www.youtube.com/playlist?list=PLLssT5z_DsK8Xwnh_0bjN4KNT81bekvtt)
- [Information Retrieval SS 2014, iTunes - HPI](https://itunes.apple.com/us/itunes-u/information-retrieval-ss-2014/id874200291)
- [MOOC - Data Mining with Weka](https://www.youtube.com/playlist?list=PLm4W7_iX_v4NqPUjceOGd-OKNVO4c_cPD)
- [Data Mining: Learning From Large Datasets - Fall 2017 - ETH Zurich](https://www.youtube.com/playlist?list=PLY-OA_xnxFwRHZO6L6yT253VPgrZazQs6)
- [Information Retrieval - Spring 2018 - ETH Zurich](https://www.youtube.com/playlist?list=PLzn6LN6WhlN1ktkDvNurPSDwTQ_oGQisn)
- [CAP6673 - Data Mining and Machine Learning - FAU](http://www.cse.fau.edu/~taghi/classes/cap6673/)([Video lectures](https://vimeo.com/album/1505953))
- [Data Warehousing and Data Mining Techniques - Technische Universität Braunschweig, Germany](http://www.ifis.cs.tu-bs.de/teaching/ws-1617/dwh)
- **Data Science**
- [Data 8: The Foundations of Data Science - UC Berkeley](http://data8.org/) ([Summer 17](http://data8.org/su17/))
- [CSE519 - Data Science Fall 2016 - Skiena, SBU](https://www.youtube.com/playlist?list=PLOtl7M3yp-DVBdLYatrltDJr56AKZ1qXo)
- [CS 109 Data Science, Harvard University](http://cs109.github.io/2015/pages/videos.html) ([YouTube](https://www.youtube.com/playlist?list=PLb4G5axmLqiuneCqlJD2bYFkBwHuOzKus))
- [6.0002 Introduction to Computational Thinking and Data Science - MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/lecture-videos/)
- [Distributed Data Analytics (WT 2017/18) - HPI University of Potsdam](https://www.tele-task.de/series/1179/)
- [Statistics 133 - Concepts in Computing with Data, Fall 2013 - UC Berkeley](https://www.youtube.com/playlist?list=PL-XXv-cvA_iDsSPnMJlnhIyADGUmikoIO)
- [Data Profiling and Data Cleansing (WS 2014/15) - HPI University of Potsdam](https://www.tele-task.de/series/1027/)
- [AM 207 - Stochastic Methods for Data Analysis, Inference and Optimization, Harvard University](http://am207.github.io/2016/index.html)
- [CS 229r - Algorithms for Big Data, Harvard University](http://people.seas.harvard.edu/~minilek/cs229r/fall15/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0v1kQTpqpuu5kEJo2i-iUyf))
- [Algorithms for Big Data - IIT Madras](https://nptel.ac.in/courses/106106142/)
- [Data 8: The Foundations of Data Science - UC Berkeley](http://data8.org/) ([Summer 17](http://data8.org/su17/))
- [CSE519 - Data Science Fall 2016 - Skiena, SBU](https://www.youtube.com/playlist?list=PLOtl7M3yp-DVBdLYatrltDJr56AKZ1qXo)
- [CS 109 Data Science, Harvard University](http://cs109.github.io/2015/pages/videos.html) ([YouTube](https://www.youtube.com/playlist?list=PLb4G5axmLqiuneCqlJD2bYFkBwHuOzKus))
- [6.0002 Introduction to Computational Thinking and Data Science - MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/lecture-videos/)
- [Distributed Data Analytics (WT 2017/18) - HPI University of Potsdam](https://www.tele-task.de/series/1179/)
- [Statistics 133 - Concepts in Computing with Data, Fall 2013 - UC Berkeley](https://www.youtube.com/playlist?list=PL-XXv-cvA_iDsSPnMJlnhIyADGUmikoIO)
- [Data Profiling and Data Cleansing (WS 2014/15) - HPI University of Potsdam](https://www.tele-task.de/series/1027/)
- [AM 207 - Stochastic Methods for Data Analysis, Inference and Optimization, Harvard University](http://am207.github.io/2016/index.html)
- [CS 229r - Algorithms for Big Data, Harvard University](http://people.seas.harvard.edu/~minilek/cs229r/fall15/lec.html) ([Youtube](https://www.youtube.com/playlist?list=PL2SOU6wwxB0v1kQTpqpuu5kEJo2i-iUyf))
- [Algorithms for Big Data - IIT Madras](https://nptel.ac.in/courses/106106142/)
- [Part 1: Practical Deep Learning for Coders, v3 - fast.ai](https://course.fast.ai/)
- [Part 2: Deep Learning from the Foundations - fast.ai](https://course19.fast.ai/part2)
- [Deep learning at Oxford 2015 - Nando de Freitas](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu)
- [6.S094: Deep Learning for Self-Driving Cars - MIT](https://www.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf)
- [CS294-129 Designing, Visualizing and Understanding Deep Neural Networks](https://bcourses.berkeley.edu/courses/1453965/pages/cs294-129-designing-visualizing-and-understanding-deep-neural-networks) ([YouTube](https://www.youtube.com/playlist?list=PLkFD6_40KJIxopmdJF_CLNqG3QuDFHQUm))
- [CS230: Deep Learning - Autumn 2018 - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb)
- [STAT-157 Deep Learning 2019 - UC Berkeley](https://www.youtube.com/playlist?list=PLZSO_6-bSqHQHBCoGaObUljoXAyyqhpFW)
- [Deep Unsupervised Learning -- Berkeley Spring 2020](https://www.youtube.com/playlist?list=PLwRJQ4m4UJjPiJP3691u-qWwPGVKzSlNP)
- [Stat 946 Deep Learning - University of Waterloo](https://www.youtube.com/playlist?list=PLehuLRPyt1Hyi78UOkMPWCGRxGcA9NVOE)
- [Neural networks class - Université de Sherbrooke](http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html) ([YouTube](https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH))
- [CS294-158 Deep Unsupervised Learning SP19](https://www.youtube.com/channel/UCf4SX8kAZM_oGcZjMREsU9w/videos)
- [DLCV - Deep Learning for Computer Vision - UPC Barcelona](https://www.youtube.com/playlist?list=PL-5eMc3HQTBavDoZpFcX-bff5WgQqSLzR)
- [DLAI - Deep Learning for Artificial Intelligence @ UPC Barcelona](https://www.youtube.com/playlist?list=PL-5eMc3HQTBagIUjKefjcTbnXC0wXC_vd)
- [Neural Networks and Applications - IIT Kharagpur](https://nptel.ac.in/courses/117105084/)
- [UVA DEEP LEARNING COURSE](http://uvadlc.github.io/#lecture)
- [Part 1: Practical Deep Learning for Coders, v3 - fast.ai](https://course.fast.ai/)
- [Part 2: Deep Learning from the Foundations - fast.ai](https://course19.fast.ai/part2)
- [Deep learning at Oxford 2015 - Nando de Freitas](https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu)
- [6.S094: Deep Learning for Self-Driving Cars - MIT](https://www.youtube.com/playlist?list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf)
- [CS294-129 Designing, Visualizing and Understanding Deep Neural Networks](https://bcourses.berkeley.edu/courses/1453965/pages/cs294-129-designing-visualizing-and-understanding-deep-neural-networks) ([YouTube](https://www.youtube.com/playlist?list=PLkFD6_40KJIxopmdJF_CLNqG3QuDFHQUm))
- [CS230: Deep Learning - Autumn 2018 - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb)
- [STAT-157 Deep Learning 2019 - UC Berkeley](https://www.youtube.com/playlist?list=PLZSO_6-bSqHQHBCoGaObUljoXAyyqhpFW)
- [Deep Unsupervised Learning -- Berkeley Spring 2020](https://www.youtube.com/playlist?list=PLwRJQ4m4UJjPiJP3691u-qWwPGVKzSlNP)
- [Stat 946 Deep Learning - University of Waterloo](https://www.youtube.com/playlist?list=PLehuLRPyt1Hyi78UOkMPWCGRxGcA9NVOE)
- [Neural networks class - Université de Sherbrooke](http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html) ([YouTube](https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH))
- [CS294-158 Deep Unsupervised Learning SP19](https://www.youtube.com/channel/UCf4SX8kAZM_oGcZjMREsU9w/videos)
- [DLCV - Deep Learning for Computer Vision - UPC Barcelona](https://www.youtube.com/playlist?list=PL-5eMc3HQTBavDoZpFcX-bff5WgQqSLzR)
- [DLAI - Deep Learning for Artificial Intelligence @ UPC Barcelona](https://www.youtube.com/playlist?list=PL-5eMc3HQTBagIUjKefjcTbnXC0wXC_vd)
- [Neural Networks and Applications - IIT Kharagpur](https://nptel.ac.in/courses/117105084/)
- [UVA DEEP LEARNING COURSE](http://uvadlc.github.io/#lecture)
- [CS294-112, Deep Reinforcement Learning Sp17](http://rll.berkeley.edu/deeprlcourse/) ([YouTube](https://www.youtube.com/playlist?list=PLkFD6_40KJIwTmSbCv9OVJB3YaO4sFwkX))
- [UCL Course 2015 on Reinforcement Learning by David Silver from DeepMind](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html) ([YouTube](https://www.youtube.com/watch?v=2pWv7GOvuf0))
- [Deep RL Bootcamp - Berkeley Aug 2017](https://sites.google.com/view/deep-rl-bootcamp/lectures)
- [CS294-112, Deep Reinforcement Learning Sp17](http://rll.berkeley.edu/deeprlcourse/) ([YouTube](https://www.youtube.com/playlist?list=PLkFD6_40KJIwTmSbCv9OVJB3YaO4sFwkX))
- [UCL Course 2015 on Reinforcement Learning by David Silver from DeepMind](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html) ([YouTube](https://www.youtube.com/watch?v=2pWv7GOvuf0))
- [Deep RL Bootcamp - Berkeley Aug 2017](https://sites.google.com/view/deep-rl-bootcamp/lectures)
- [18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT](https://www.youtube.com/playlist?list=PLB3sDpSRdrOvI1hYXNsa6Lety7K8FhPpx)
- [CS 330 - Deep Multi-Task and Meta Learning - Fall 2019 - Stanford University](https://cs330.stanford.edu/) ([Youtube](https://www.youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5))
- [Machine Learning 2013 - Nando de Freitas, UBC](https://www.youtube.com/playlist?list=PLE6Wd9FR--EdyJ5lbFl8UuGjecvVw66F6)
- [Machine Learning, 2014-2015, University of Oxford](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
- [10-702/36-702 - Statistical Machine Learning - Larry Wasserman, Spring 2016, CMU](https://www.stat.cmu.edu/~ryantibs/statml/) ([Spring 2015](https://www.youtube.com/playlist?list=PLjbUi5mgii6BWEUZf7He6nowWvGne_Y8r))
- [10-715 Advanced Introduction to Machine Learning - CMU](http://www.cs.cmu.edu/~bapoczos/Classes/ML10715_2015Fall/) ([YouTube](https://www.youtube.com/playlist?list=PL4DwY1suLMkcu-wytRDbvBNmx57CdQ2pJ))
- [18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT](https://www.youtube.com/playlist?list=PLB3sDpSRdrOvI1hYXNsa6Lety7K8FhPpx)
- [CS 330 - Deep Multi-Task and Meta Learning - Fall 2019 - Stanford University](https://cs330.stanford.edu/) ([Youtube](https://www.youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5))
- **ML based Natural Language Processing and Computer Vision**
- [CS 224d - Deep Learning for Natural Language Processing, Stanford University](http://cs224d.stanford.edu/syllabus.html) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLCJlDcMjVoEdtem5GaohTC1o9HTTFtK7_))
- [CS 124 - From Languages to Information - Stanford University](https://www.youtube.com/channel/UC_48v322owNVtORXuMeRmpA/playlists?view=50&sort=dd&shelf_id=2)
- [MOOC - Natural Language Processing, Dan Jurafsky & Chris Manning - Coursera](https://www.youtube.com/playlist?list=PL6397E4B26D00A269)
- [fast.ai Code-First Intro to Natural Language Processing](https://www.youtube.com/playlist?list=PLtmWHNX-gukKocXQOkQjuVxglSDYWsSh9) ([Github](https://github.com/fastai/course-nlp))
- [MOOC - Natural Language Processing - Coursera, University of Michigan](https://www.youtube.com/playlist?list=PLLssT5z_DsK8BdawOVCCaTCO99Ya58ryR)
- [CS224U: Natural Language Understanding - Spring 2019 - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rObpMCir6rNNUlFAn56Js20)
- [Deep Learning for Natural Language Processing, 2017 - Oxford University](https://github.com/oxford-cs-deepnlp-2017/lectures)
- [Machine Learning for Robotics and Computer Vision, WS 2013/2014 - TU München](https://vision.in.tum.de/teaching/ws2013/ml_ws13) ([YouTube](https://www.youtube.com/playlist?list=PLTBdjV_4f-EIiongKlS9OKrBEp8QR47Wl))
- [Informatics 1 - Cognitive Science 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/inf1cs.htm)
- [Informatics 2A - Processing Formal and Natural Languages 2016-17 - University of Edinburgh](http://www.inf.ed.ac.uk/teaching/courses/inf2a/schedule.html)
- [Computational Cognitive Science 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/ccs.htm)
- [Accelerated Natural Language Processing 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/anlp.htm)
- [Natural Language Processing - IIT Bombay](https://nptel.ac.in/courses/106101007/)
- [NOC:Deep Learning For Visual Computing - IIT Kharagpur](https://nptel.ac.in/courses/108/105/108105103/)
- [Natural Language Processing - Michael Collins - Columbia University](https://www.youtube.com/playlist?list=PLA212ij5XG8OTDRl8IWFiJgHR9Ve2k9pv)
- [Deep Learning for Computer Vision - University of Michigan](https://www.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r)
- [CMU CS11-737 - Multilingual Natural Language Processing](https://www.youtube.com/playlist?list=PL8PYTP1V4I8CHhppU6n1Q9-04m96D9gt5)
- [CS 224d - Deep Learning for Natural Language Processing, Stanford University](http://cs224d.stanford.edu/syllabus.html) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLCJlDcMjVoEdtem5GaohTC1o9HTTFtK7_))
- [CS 124 - From Languages to Information - Stanford University](https://www.youtube.com/channel/UC_48v322owNVtORXuMeRmpA/playlists?view=50&sort=dd&shelf_id=2)
- [MOOC - Natural Language Processing, Dan Jurafsky & Chris Manning - Coursera](https://www.youtube.com/playlist?list=PL6397E4B26D00A269)
- [fast.ai Code-First Intro to Natural Language Processing](https://www.youtube.com/playlist?list=PLtmWHNX-gukKocXQOkQjuVxglSDYWsSh9) ([Github](https://github.com/fastai/course-nlp))
- [MOOC - Natural Language Processing - Coursera, University of Michigan](https://www.youtube.com/playlist?list=PLLssT5z_DsK8BdawOVCCaTCO99Ya58ryR)
- [CS224U: Natural Language Understanding - Spring 2019 - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rObpMCir6rNNUlFAn56Js20)
- [Deep Learning for Natural Language Processing, 2017 - Oxford University](https://github.com/oxford-cs-deepnlp-2017/lectures)
- [Machine Learning for Robotics and Computer Vision, WS 2013/2014 - TU München](https://vision.in.tum.de/teaching/ws2013/ml_ws13) ([YouTube](https://www.youtube.com/playlist?list=PLTBdjV_4f-EIiongKlS9OKrBEp8QR47Wl))
- [Informatics 1 - Cognitive Science 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/inf1cs.htm)
- [Informatics 2A - Processing Formal and Natural Languages 2016-17 - University of Edinburgh](http://www.inf.ed.ac.uk/teaching/courses/inf2a/schedule.html)
- [Computational Cognitive Science 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/ccs.htm)
- [Accelerated Natural Language Processing 2015/16- University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/anlp.htm)
- [Natural Language Processing - IIT Bombay](https://nptel.ac.in/courses/106101007/)
- [NOC:Deep Learning For Visual Computing - IIT Kharagpur](https://nptel.ac.in/courses/108/105/108105103/)
- [Natural Language Processing - Michael Collins - Columbia University](https://www.youtube.com/playlist?list=PLA212ij5XG8OTDRl8IWFiJgHR9Ve2k9pv)
- [Deep Learning for Computer Vision - University of Michigan](https://www.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r)
- [CMU CS11-737 - Multilingual Natural Language Processing](https://www.youtube.com/playlist?list=PL8PYTP1V4I8CHhppU6n1Q9-04m96D9gt5)
- **Time Series Analysis**
- [02417 Time Series Analysis](https://www.youtube.com/playlist?list=PLtiTxpFJ4k6TZ0g496fVcQpt_-XJRNkbi)
- [Applied Time Series Analysis](https://www.youtube.com/playlist?list=PLl0FT6O_WWDBm-4W-eoK34omYmEMseQDX)
- [02417 Time Series Analysis](https://www.youtube.com/playlist?list=PLtiTxpFJ4k6TZ0g496fVcQpt_-XJRNkbi)
- [Applied Time Series Analysis](https://www.youtube.com/playlist?list=PLl0FT6O_WWDBm-4W-eoK34omYmEMseQDX)
- **Misc Machine Learning Topics**
- [EE364a: Convex Optimization I - Stanford University](http://web.stanford.edu/class/ee364a/videos.html)
- [CS 6955 - Clustering, Spring 2015, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCpRvi-qSMCdOwyn4UYoPxTI)
- [Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information](http://blogs.ischool.berkeley.edu/i290-abdt-s12/) ([YouTube](https://www.youtube.com/playlist?list=PLE8C1256A28C1487F))
- [10-725 Convex Optimization, Spring 2015 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt-S15/)
- [10-725 Convex Optimization: Fall 2016 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt/)
- [CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas](http://granite.ices.utexas.edu/coursewiki/index.php/Main_Page)
- [CS224W Machine Learning with Graphs | Spring 2021 | Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn)
- [9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT](https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O)
- [Statistical Rethinking Winter 2015 - Richard McElreath](https://www.youtube.com/playlist?list=PLDcUM9US4XdMdZOhJWJJD4mDBMnbTWw_z)
- [Music Information Retrieval - University of Victoria, 2014](http://marsyas.cs.uvic.ca/mirBook/course/)
- [PURDUE Machine Learning Summer School 2011](https://www.youtube.com/playlist?list=PL2A65507F7D725EFB)
- [Foundations of Machine Learning - Blmmoberg Edu](https://bloomberg.github.io/foml/#home)
- [Introduction to reinforcement learning - UCL](https://www.youtube.com/playlist?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ)
- [Advanced Deep Learning & Reinforcement Learning - UCL](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs)
- [Web Information Retrieval (Proff. L. Becchetti - A. Vitaletti)](https://www.youtube.com/playlist?list=PLAQopGWlIcya-9yzQ8c8UtPOuCv0mFZkr)
- [Big Data Systems (WT 2019/20) - Prof. Dr. Tilmann Rabl - HPI](https://www.tele-task.de/series/1286/)
- [Distributed Data Analytics (WT 2017/18) - Dr. Thorsten Papenbrock - HPI](https://www.tele-task.de/series/1179/)
- [EE364a: Convex Optimization I - Stanford University](http://web.stanford.edu/class/ee364a/videos.html)
- [CS 6955 - Clustering, Spring 2015, University of Utah](https://www.youtube.com/playlist?list=PLbuogVdPnkCpRvi-qSMCdOwyn4UYoPxTI)
- [Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information](http://blogs.ischool.berkeley.edu/i290-abdt-s12/) ([YouTube](https://www.youtube.com/playlist?list=PLE8C1256A28C1487F))
- [10-725 Convex Optimization, Spring 2015 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt-S15/)
- [10-725 Convex Optimization: Fall 2016 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt/)
- [CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas](http://granite.ices.utexas.edu/coursewiki/index.php/Main_Page)
- [CS224W Machine Learning with Graphs | Spring 2021 | Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn)
- [9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT](https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O)
- [Statistical Rethinking Winter 2015 - Richard McElreath](https://www.youtube.com/playlist?list=PLDcUM9US4XdMdZOhJWJJD4mDBMnbTWw_z)
- [Music Information Retrieval - University of Victoria, 2014](http://marsyas.cs.uvic.ca/mirBook/course/)
- [PURDUE Machine Learning Summer School 2011](https://www.youtube.com/playlist?list=PL2A65507F7D725EFB)
- [Foundations of Machine Learning - Blmmoberg Edu](https://bloomberg.github.io/foml/#home)
- [Introduction to reinforcement learning - UCL](https://www.youtube.com/playlist?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ)
- [Advanced Deep Learning & Reinforcement Learning - UCL](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs)
- [Web Information Retrieval (Proff. L. Becchetti - A. Vitaletti)](https://www.youtube.com/playlist?list=PLAQopGWlIcya-9yzQ8c8UtPOuCv0mFZkr)
- [Big Data Systems (WT 2019/20) - Prof. Dr. Tilmann Rabl - HPI](https://www.tele-task.de/series/1286/)
- [Distributed Data Analytics (WT 2017/18) - Dr. Thorsten Papenbrock - HPI](https://www.tele-task.de/series/1179/)
------------------------------
### Computer Networks
### Computer Networks
- [14-740 - Fundamentals of Computer Networks - CMU](http://www.ini740.com/)
- [CS 144 Introduction to Computer Networking - Stanford University, Fall 2013](http://www.scs.stanford.edu/10au-cs144/) ([Lecture videos](https://www.youtube.com/playlist?list=PLvFG2xYBrYAQCyz4Wx3NPoYJOFjvU7g2Z))
- [Computer Communication Networks, Rensselaer Polytechnic Institute - Fall 2001](https://www.ecse.rpi.edu/Homepages/koushik/shivkuma-teaching/video_index.html) ([Videos](https://www.ecse.rpi.edu/Homepages/koushik/shivkuma-teaching/video_index.html#ccn_video)) ([Slides](https://www.ecse.rpi.edu/Homepages/koushik/shivkuma-teaching/video_index.html#ccn_foils))
@ -487,10 +488,12 @@ Table of Contents
- [Internetworking with TCP/IP by Prof. Dr. Christoph Meinel - HPI](https://www.youtube.com/playlist?list=PLoOmvuyo5UAfY5VrkObHTckZHwPsS1VCA)
- [CS798: Mathematical Foundations of Computer Networking - University of Waterloo](https://www.youtube.com/playlist?list=PLFB088DB91845CA34)
------------------------------
### Math for Computer Scientist
-------------------------
### Math for Computer Scientist
- [List of Science & Math courses with video lectures](https://github.com/Developer-Y/math-science-video-lectures)
- [Maths courses all topics covered](https://www.khanacademy.org/math/)
- **Calculus**
- [18.01 Single Variable Calculus, Fall 2006 - MIT OCW](https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/)
@ -540,10 +543,10 @@ Table of Contents
- [Statistical Computing, Fall 2017 - Notre Dame](https://www.youtube.com/playlist?list=PLd-PuDzW85AcSgNGnT5TUHt85SrCljT3V)
- [Mathematics for Machine Learning, Lectures by Ulrike von Luxburg - Tübingen Machine Learning](https://www.youtube.com/playlist?list=PL05umP7R6ij1a6KdEy8PVE9zoCv6SlHRS)
------------------------------
### Web Programming and Internet Technologies
-------------------------
### Web Programming and Internet Technologies
- [Web Design Decal - HTML/CSS/JavaScript Course, University of California, Berkeley](http://live.wdd.io/)
- [CS 75 Building Dynamic Websites - Harvard University](http://cs75.tv/2012/summer/)
- [EE319K Embedded Systems - UT Austin](http://users.ece.utexas.edu/~valvano/Volume1/E-Book/VideoLinks.htm)
- [EE445L Embedded Systems Design Lab, Fall 2015, UTexas](https://www.youtube.com/playlist?list=PLyg2vmIzGxXGBxFu8nvX3KBadSdsNAvbA)
- [CS149 Embedded Systems - Fall 2014 - UCBerkeley](https://www.youtube.com/playlist?list=PL-XXv-cvA_iDq3FCoYLeUL-X-NUlT405n)
- [ECE 4760 Designing with Microcontrollers Fall 2016, Cornell University](http://people.ece.cornell.edu/land/courses/ece4760/) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLKcjQ_UFkrd4I5WOIxHEYZ7iY04lj15Ez))
- [ECE 5760 - Advanced Microcontroller Design and system-on-chip, Spring 2016 - Cornell University](http://people.ece.cornell.edu/land/courses/ece5760/)
- [CSE 438/598 Embedded Systems Programming ASU](http://rts.lab.asu.edu/web_438_Fall_2014/CSE438_Fall2014_Main_page.htm)
- [Summer Short Course on Embedded Systems Programming](http://rts.lab.asu.edu/web_ESP_Summer2014/ESP_Main_page.htm)
- [Internet of Things by Prof. Dr.-Ing. Dietmar P. F. Möller](https://video.tu-clausthal.de/vorlesung/408.html)
- [CSE 351 - The Hardware/Software Interface, Spring 16 - University of Washington](https://courses.cs.washington.edu/courses/cse351/16sp/videos.html) ([Coursera](http://academictorrents.com/details/f1384286c8581bffba11e378fdb37608e649d82a))
- [ECE 5030 - Electronic Bioinstrumentation, Spring 2014 - Cornell University ](http://people.ece.cornell.edu/land/courses/ece5030/)
- [ECE/CS 5780/6780 - Embedded Systems Design, Spring 14 - University of Utah](https://www.youtube.com/playlist?list=PLQefpK95HyFmao3zi-WDOMkeSev-Je5dE)
- [Embedded Systems Class - Version 1 - 2011 - UNCC](https://www.youtube.com/playlist?list=PLE4462C1C306E2EB2)
- [Embedded Systems using the Renesas RX63N Processor - Version 3 - UNCC](https://www.youtube.com/playlist?list=PLPIqCiMhcdO5gxLJWt_hY5CPMzqg75IU5)
- [ELEC2142 - Embedded Systems Design - UNSW](http://eemedia.ee.unsw.edu.au/ELEC2142/index.htm)
- [Software Engineering for Embedded Systems (WS 2011/12) - HPI Univesrity of Potsdam](https://www.tele-task.de/series/864/)
- [Embedded Systems - IIT Delhi](https://nptel.ac.in/courses/108102045/)
- [Embedded Systems Design - IIT Kharagpur](https://nptel.ac.in/courses/106105159/)
- [ARM Based Development - IIT Madras](https://nptel.ac.in/courses/117106111/)
- [Software Engineering for Self Adaptive Systems - iTunes - HPI Univesrity of Potsdam](https://itunes.apple.com/us/itunes-u/software-engineering-for-self/id993578475)
- [EE260 Embedded Systems by Robert Paz](https://www.youtube.com/playlist?list=PLnvE9iJk1wvib_pdUPdQGYZrkrmg9mf__)
- [NOC:Design for internet of things - IISc Bangalore](https://nptel.ac.in/courses/108/108/108108098/)
- [EE319K Embedded Systems - UT Austin](http://users.ece.utexas.edu/~valvano/Volume1/E-Book/VideoLinks.htm)
- [EE445L Embedded Systems Design Lab, Fall 2015, UTexas](https://www.youtube.com/playlist?list=PLyg2vmIzGxXGBxFu8nvX3KBadSdsNAvbA)
- [CS149 Embedded Systems - Fall 2014 - UCBerkeley](https://www.youtube.com/playlist?list=PL-XXv-cvA_iDq3FCoYLeUL-X-NUlT405n)
- [ECE 4760 Designing with Microcontrollers Fall 2016, Cornell University](http://people.ece.cornell.edu/land/courses/ece4760/) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLKcjQ_UFkrd4I5WOIxHEYZ7iY04lj15Ez))
- [ECE 5760 - Advanced Microcontroller Design and system-on-chip, Spring 2016 - Cornell University](http://people.ece.cornell.edu/land/courses/ece5760/)
- [CSE 438/598 Embedded Systems Programming ASU](http://rts.lab.asu.edu/web_438_Fall_2014/CSE438_Fall2014_Main_page.htm)
- [Summer Short Course on Embedded Systems Programming](http://rts.lab.asu.edu/web_ESP_Summer2014/ESP_Main_page.htm)
- [Internet of Things by Prof. Dr.-Ing. Dietmar P. F. Möller](https://video.tu-clausthal.de/vorlesung/408.html)
- [CSE 351 - The Hardware/Software Interface, Spring 16 - University of Washington](https://courses.cs.washington.edu/courses/cse351/16sp/videos.html) ([Coursera](http://academictorrents.com/details/f1384286c8581bffba11e378fdb37608e649d82a))
- [ECE/CS 5780/6780 - Embedded Systems Design, Spring 14 - University of Utah](https://www.youtube.com/playlist?list=PLQefpK95HyFmao3zi-WDOMkeSev-Je5dE)
- [Embedded Systems Class - Version 1 - 2011 - UNCC](https://www.youtube.com/playlist?list=PLE4462C1C306E2EB2)
- [Embedded Systems using the Renesas RX63N Processor - Version 3 - UNCC](https://www.youtube.com/playlist?list=PLPIqCiMhcdO5gxLJWt_hY5CPMzqg75IU5)
- [ELEC2142 - Embedded Systems Design - UNSW](http://eemedia.ee.unsw.edu.au/ELEC2142/index.htm)
- [Software Engineering for Embedded Systems (WS 2011/12) - HPI University of Potsdam](https://www.tele-task.de/series/864/)
- [Embedded Systems - IIT Delhi](https://nptel.ac.in/courses/108102045/)
- [Embedded Systems Design - IIT Kharagpur](https://nptel.ac.in/courses/106105159/)
- [ARM Based Development - IIT Madras](https://nptel.ac.in/courses/117106111/)
- [Software Engineering for Self Adaptive Systems - iTunes - HPI University of Potsdam](https://itunes.apple.com/us/itunes-u/software-engineering-for-self/id993578475)
- [EE260 Embedded Systems by Robert Paz](https://www.youtube.com/playlist?list=PLnvE9iJk1wvib_pdUPdQGYZrkrmg9mf__)
- [CS1 - Higher Computing - Richard Buckland UNSW](https://www.youtube.com/playlist?list=PL6B940F08B9773B9F)
- [MOOC - From NAND to Tetris - Building a Modern Computer From First Principles](https://www.nand2tetris.org/) ([YouTube](https://www.youtube.com/playlist?list=PLNMIACtpT9BfztU0P92qlw8Gd4vxvvfT1))
- [MOOC - From NAND to TetrisBuilding a Modern Computer From First Principles](https://www.nand2tetris.org/) ([YouTube](https://www.youtube.com/playlist?list=PLNMIACtpT9BfztU0P92qlw8Gd4vxvvfT1))
- [System Validation, TU Delft](https://ocw.tudelft.nl/courses/system-validation/)
- [Introduction to ARM - Open SecurityTraining](https://www.youtube.com/playlist?list=PLUFkSN0XLZ-n91t_AX5zO007Giz1INwPd)
@ -696,14 +702,14 @@ Table of Contents
- [Onur Mutlu @ TU Wien 2019 - Memory Systems](https://www.youtube.com/playlist?list=PL5Q2soXY2Zi_gntM55VoMlKlw7YrXOhbl)
- [Memory Systems Course - Technion, Summer 2018](https://www.youtube.com/playlist?list=PL5Q2soXY2Zi-IymxXpH_9vlZCOeA7Yfn9)
------------------------------
### Security
-------
### Security
- [Internet Security (WT 2018/19) - HPI University of Potsdam](https://www.tele-task.de/series/1227/)
- [6.858 Computer Systems Security - MIT OCW](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-858-computer-systems-security-fall-2014/video-lectures/)
- [6.875 - Cryptography - Spring 2018- MIT](https://www.youtube.com/playlist?list=PL6ogFv-ieghe8MOIcpD6UDtdK-UMHG8oH)
- [6.875 - Cryptography - Spring 2018- MIT](https://www.youtube.com/playlist?list=PL6ogFv-ieghe8MOIcpD6UDtdK-UMHG8oH)
- [CSEP590A - Practical Aspects of Modern Cryptography, Winter 2011 - University of Washington](https://courses.cs.washington.edu/courses/csep590a/11wi/) ([Videos](https://courses.cs.washington.edu/courses/csep590a/11wi/video/))
- [CS461/ECE422 - Computer Security - University of Illinois at Urbana-Champaign](https://courses.engr.illinois.edu/cs461/sp2016/) ([Videos](https://recordings.engineering.illinois.edu:8443/ess/portal/section/8a560718-345a-417a-b665-6bd375a71ee2))
- [Introduction to Cryptography, Christof Paar - Ruhr University Bochum, Germany](https://www.youtube.com/playlist?list=PLwJWuZfL_Ga2KJrTf9hOIgAQWkSpn9RNm)
@ -727,17 +733,17 @@ Table of Contents
- [CSN11123 - Advanced Cloud and Network Forensics - Bill Buchanan - Edinburgh Napier](https://asecuritysite.com/csn11123)
- [CSN11117 - e-Security - Bill Buchanan - Edinburgh Napier](https://asecuritysite.com/csn11117)
- [CSN08704 - Telecommunications - Bill Buchanan - Edinburgh Napier](https://asecuritysite.com/csn08704)
- [CSN11128 - Incident Response and Malware Analysis - Bill Buchanan - Edinburgh Napier](https://asecuritysite.com/CSN11128)
- [CSN11128 - Incident Response and Malware Analysus - Bill Buchanan - Edinburgh Napier](https://asecuritysite.com/CSN11128)
- [Internet Security for Beginners by Dr. Christoph Meinel - HPI](https://www.youtube.com/playlist?list=PLoOmvuyo5UAdsi-IacgZJQF1MRw0Ee-HH)
------------------------------
-------
### Computer Graphics
- [CS184 - Computer Graphics, Fall 2012 - UC Berkeley](http://inst.eecs.berkeley.edu/~cs184/fa12/onlinelectures.html)
- [Image Processing and Analysis - UC Davis](https://www.youtube.com/playlist?list=PLA64AFAE28B8DD0FD)
- [CS 543 - Computer Vision – Spring 2017](https://courses.engr.illinois.edu/cs543/sp2017/) ([Recordings](https://echo360.org/section/283b0471-3d9f-4efb-9c51-bc00e778735e/home))
- [CAP 5415 - Computer Vision - University of Central Florida](https://www.crcv.ucf.edu/courses/cap5415-fall-2012/)([Video Lectures](https://www.youtube.com/playlist?list=PLd3hlSJsX_ImKP68wfKZJVIPTd8Ie5u-9))
- [EE225B - Digital Image Processing, Spring 2014 - UC Berkeley](https://inst.eecs.berkeley.edu/~ee225b/sp14/) ([Videos - Spring 2006](http://www-video.eecs.berkeley.edu/~avz/video_225b.html))
- [EE637 - Digital Image Processing I - Purdue University](https://engineering.purdue.edu/~bouman/ece637/) ([Videos - Sp 2011](https://www.youtube.com/user/ModelBasedImaging),[Videos - Sp 2007](https://engineering.purdue.edu/~bouman/ece637/lectures/lectures07/))
- [EE637 - Digital Image Processing I - Purdue University](https://engineering.purdue.edu/~bouman/ece637/) ([Videos - Sp 2011](https://www.youtube.com/user/ModelBasedImaging),[Videos - Sp 2007](https://engineering.purdue.edu/~bouman/ece637/lectures/lectures07/))
- [Computer Vision I: Variational Methods - TU München](https://vision.in.tum.de/teaching/ws2015/vmcv2015) ([YouTube](https://www.youtube.com/playlist?list=PLTBdjV_4f-EJ7A2iIH5L5ztqqrWYjP2RI))
- [Computer Vision II: Multiple View Geometry (IN2228), SS 2016 - TU München](https://vision.in.tum.de/teaching/ss2016/mvg2016) ([YouTube](https://www.youtube.com/playlist?list=PLTBdjV_4f-EJn6udZ34tht9EVIW7lbeo4))
- [EGGN 510 - Image and Multidimensional Signal Processing - Colorado School of Mines](http://inside.mines.edu/~whoff/courses/EENG510/lectures/)
@ -777,7 +783,7 @@ Table of Contents
- [Photogrammetry Course - 2015/16 - University of Bonn, Germany](https://www.youtube.com/playlist?list=PLgnQpQtFTOGRsi5vzy9PiQpNWHjq-bKN1)
- [MOOC - Introduction to Computer Vision - Udacity](https://www.youtube.com/playlist?list=PLAwxTw4SYaPnbDacyrK_kB_RUkuxQBlCm)
- [ECSE-4540 - Intro to Digital Image Processing - Spring 2015 - RPI](https://www.youtube.com/playlist?list=PLuh62Q4Sv7BUf60vkjePfcOQc8sHxmnDX)
- [Photogrammetry 1 Course – 2020 - University of Bonn](https://www.ipb.uni-bonn.de/photo1-2020/)
- [Photogrammetry II Course 2020/21 - University of Bonn](https://www.ipb.uni-bonn.de/photo2-2020/)
------------------------------
### Computational Biology
--------------------------------
### Computational Biology
- [ECS 124 - Foundations of Algorithms for Bioinformatics - Dan Gusfield, UC Davis](http://web.cs.ucdavis.edu/~gusfield/cs124videos/videolist.html) ([YouTube](https://www.youtube.com/playlist?list=PL_w_qWAQZtAbh8bHfzXYpdnVKCGCDmmoL))
- [Introduction to Machine Vision](https://www.youtube.com/playlist?list=PL1pxneANaikCO1-Z0XTaljLR3SE8tgRXY)
- [6.834J Cognitive Robotics - MIT OCW](https://ocw.mit.edu/courses/aeronautics-and-astronautics/16-412j-cognitive-robotics-spring-2016/)
- [6.834J Cognitive Robotics - MIT OCW](https://ocw.mit.edu/courses/aeronautics-and-astronautics/16-412j-cognitive-robotics-spring-2016/)
- [Hello (Real) World with ROS – Robot Operating System - TU Delft](https://ocw.tudelft.nl/courses/hello-real-world-ros-robot-operating-system/)
- [Programming for Robotics (ROS) - ETH Zurich](https://www.youtube.com/playlist?list=PLE-BQwvVGf8HOvwXPgtDfWoxd4Cc6ghiP)
- [Mechatronic System Design - TU Delft](https://ocw.tudelft.nl/courses/mechatronic-system-design/)
@ -868,11 +872,12 @@ Table of Contents
- [Introduction to Mobile Robotics - SS 2019 - Universität Freiburg](http://ais.informatik.uni-freiburg.de/teaching/ss19/robotics/)
- [Robot Mapping - WS 2018/19 - Universität Freiburg](http://ais.informatik.uni-freiburg.de/teaching/ws18/mapping/)
- [Mechanism and Robot Kinematics - IIT Kharagpur](https://nptel.ac.in/courses/112/105/112105236/)
- [Self-Driving Cars - Cyrill Stachniss - Winter 2020/21 - University of Bonn)](https://www.youtube.com/playlist?list=PLgnQpQtFTOGQo2Z_ogbonywTg8jxCI9pD)
- [Self-Driving Cars - Cyrill Stachniss - Winter 2020/21 - University of Bonn)](https://www.youtube.com/playlist?list=PLgnQpQtFTOGQo2Z_ogbonywTg8jxCI9pD)
- [Mobile Sensing and Robotics 1 – Part Stachniss (Jointly taught with PhoRS) - University of Bonn](https://www.ipb.uni-bonn.de/msr1-2020/)
- [Mobile Sensing and Robotics 2 – Stachniss & Klingbeil/Holst - University of Bonn](https://www.ipb.uni-bonn.de/msr2-2020/)
------------------------------
----------------------------------
### Computational Finance
@ -884,16 +889,18 @@ Table of Contents
- [ACT 460 / STA 2502 – Stochastic Methods for Actuarial Science - University of Toronto](http://www.utstat.utoronto.ca/sjaimung/courses/sta2502/main.htm)
- [MMF1928H / STA 2503F –
Pricing Theory I / Applied Probability for Mathematical Finance - University of Toronto](http://www.utstat.toronto.edu/sjaimung/courses/mmf1928/content2013.htm)
- [STA 4505H – High Frequency & Algorithmic trading - University of Toronto](http://www.utstat.utoronto.ca/sjaimung/courses/sta4505/main-2014.htm)
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