- [Semantic Web Technologies by Dr. Harald Sack - HPI](https://www.youtube.com/playlist?list=PLoOmvuyo5UAeihlKcWpzVzB51rr014TwD)
- [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)
- [Knowledge Engineering with Semantic Web Technologies by Dr. Harald Sack - HPI](https://www.youtube.com/playlist?list=PLoOmvuyo5UAcBXlhTti7kzetSsi1PpJGR)
- [T81-558: Applications of Deep Neural Networks by Jeff Heaton, 2022, Washington University in St. Louis](https://sites.wustl.edu/jeffheaton/t81-558/)
- [T81-558: Applications of Deep Neural Networks by Jeff Heaton, 2022, Washington University in St. Louis](https://sites.wustl.edu/jeffheaton/t81-558/)
- [MSU programming for AI](https://www.youtube.com/playlist?list=PLZ-krWGO-UEz84TseDMIlx2Set6xZp0YP)
------------------------------
------------------------------
@ -402,6 +403,7 @@ Table of Contents
- [MIT 6.036 Introduction to Machine Learning spring 2019, by Leslie Kaelbling](https://www.youtube.com/playlist?list=PLQEw29vp6f1Ae9dp8vkKB8H6sF1PHvP5N)
- [MIT 6.036 Introduction to Machine Learning spring 2019, by Leslie Kaelbling](https://www.youtube.com/playlist?list=PLQEw29vp6f1Ae9dp8vkKB8H6sF1PHvP5N)
- [UCLA STAT C161 Introduction to Pattern Recognition and Machine Learning winter 2023, by Arash Amini](https://www.youtube.com/playlist?list=PLN_qg0-2-0SwLCXGUyM3FNSRwG6GNgONr)
- [UCLA STAT C161 Introduction to Pattern Recognition and Machine Learning winter 2023, by Arash Amini](https://www.youtube.com/playlist?list=PLN_qg0-2-0SwLCXGUyM3FNSRwG6GNgONr)
- [UT Austin Machine Learning Algorithms & Statistical Learning by Adam Klivans & Qiang Liu](https://www.youtube.com/playlist?list=PL682UO4IMem-57hfHijQyk24vR9wq7CWV)
- [UT Austin Machine Learning Algorithms & Statistical Learning by Adam Klivans & Qiang Liu](https://www.youtube.com/playlist?list=PL682UO4IMem-57hfHijQyk24vR9wq7CWV)
- [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))
- [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 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))
@ -504,6 +506,8 @@ Table of Contents
- [18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT](https://www.youtube.com/playlist?list=PLB3sDpSRdrOvI1hYXNsa6Lety7K8FhPpx)
- [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))
- [CS 330 - Deep Multi-Task and Meta Learning - Fall 2019 - Stanford University](https://cs330.stanford.edu/) ([Youtube](https://www.youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5))
- [Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022](https://www.youtube.com/playlist?list=PLoROMvodv4rNjRoawgt72BBNwL2V7doGI)
- [Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022](https://www.youtube.com/playlist?list=PLoROMvodv4rNjRoawgt72BBNwL2V7doGI)
- [02417 Time Series Analysis](https://www.youtube.com/playlist?list=PLtiTxpFJ4k6TZ0g496fVcQpt_-XJRNkbi)
- [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)
- [Applied Time Series Analysis](https://www.youtube.com/playlist?list=PLl0FT6O_WWDBm-4W-eoK34omYmEMseQDX)
@ -664,6 +669,7 @@ Table of Contents
- [INTRODUCTION TO MATRIX ALGEBRA](http://ma.mathforcollege.com/youtube/index.html)
- [INTRODUCTION TO MATRIX ALGEBRA](http://ma.mathforcollege.com/youtube/index.html)
- [Computational Linear Algebra - fast.ai](https://www.youtube.com/playlist?list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY) ([Github](https://github.com/fastai/numerical-linear-algebra))
- [Computational Linear Algebra - fast.ai](https://www.youtube.com/playlist?list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY) ([Github](https://github.com/fastai/numerical-linear-algebra))
- [ENGR108: Introduction to Applied Linear Algebra—Vectors, Matrices, and Least Squares - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rMz-WbFQtNUsUElIh2cPmN9)
- [ENGR108: Introduction to Applied Linear Algebra—Vectors, Matrices, and Least Squares - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rMz-WbFQtNUsUElIh2cPmN9)
- [MIT 18.S096 Matrix Calculus For Machine Learning And Beyond](https://www.youtube.com/playlist?list=PLUl4u3cNGP62EaLLH92E_VCN4izBKK6OE)
- [10-600 Math Background for ML - CMU](https://www.youtube.com/playlist?list=PL7y-1rk2cCsA339crwXMWUaBRuLBvPBCg)
- [10-600 Math Background for ML - CMU](https://www.youtube.com/playlist?list=PL7y-1rk2cCsA339crwXMWUaBRuLBvPBCg)
- [MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning](https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/video-lectures/)
- [MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning](https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/video-lectures/)
- [Direct Methods for Sparse Linear Systems - Prof Tim Davis - UFL](https://www.youtube.com/playlist?list=PL5EvFKC69QIyRLFuxWRnH6hIw6e1-bBXB)
- [Direct Methods for Sparse Linear Systems - Prof Tim Davis - UFL](https://www.youtube.com/playlist?list=PL5EvFKC69QIyRLFuxWRnH6hIw6e1-bBXB)
@ -693,6 +699,7 @@ Table of Contents
- [Fundamental Mathematics for Robotics spring 2020, by Ken Tomiyama](https://www.youtube.com/@citqualityeducation803/videos)
- [Fundamental Mathematics for Robotics spring 2020, by Ken Tomiyama](https://www.youtube.com/@citqualityeducation803/videos)
- [Short Course on Casual Inference, by Sanjay Shakkottai](https://www.youtube.com/playlist?list=PLcip-Gs_jEK_l2pNG8V_0UDK9jyPtLyuq)
- [Short Course on Casual Inference, by Sanjay Shakkottai](https://www.youtube.com/playlist?list=PLcip-Gs_jEK_l2pNG8V_0UDK9jyPtLyuq)
- [UCLA STAT 100C Linear Models spring 2023, by Arash Amini](https://www.youtube.com/playlist?list=PLN_qg0-2-0SzrzpEoojAa4anJdaKa49GM)
- [UCLA STAT 100C Linear Models spring 2023, by Arash Amini](https://www.youtube.com/playlist?list=PLN_qg0-2-0SzrzpEoojAa4anJdaKa49GM)
- [MSU Math for Computing](https://www.youtube.com/playlist?list=PLZ-krWGO-UEyLqtyA2pACX_tXXBTLWkI1)
------------------------------
------------------------------
@ -956,6 +963,7 @@ Table of Contents
### Computational Physics
### Computational Physics
- [Statistics and Machine Learning for Astronomy](https://www.youtube.com/playlist?list=PLo4wAAMJnA1wDQ2ZmTJCaBYdrXqBWUwT5)
- [Astronomical data analysis using Python 2021 - NRC IUCAA](https://www.youtube.com/playlist?list=PL3jLiVc5sr3P7Uov0VFsEfwPOEG1rF-FO)
- [Astronomical data analysis using Python 2021 - NRC IUCAA](https://www.youtube.com/playlist?list=PL3jLiVc5sr3P7Uov0VFsEfwPOEG1rF-FO)
- [SPARC Workshop on Machine Learning in Solar Physics and Space Weather - CESSI IISER Kolkata](https://www.youtube.com/playlist?list=PLtxxbMktGS8pjURPBXJTAkClnXVE_ZNni)
- [SPARC Workshop on Machine Learning in Solar Physics and Space Weather - CESSI IISER Kolkata](https://www.youtube.com/playlist?list=PLtxxbMktGS8pjURPBXJTAkClnXVE_ZNni)
- [Data-Driven Methods and Machine Learning in Atmospheric Sciences - IISC](https://www.youtube.com/playlist?list=PLnUDCXHuQXBaGrYSbDMWi2inp7GSe3__8)
- [Data-Driven Methods and Machine Learning in Atmospheric Sciences - IISC](https://www.youtube.com/playlist?list=PLnUDCXHuQXBaGrYSbDMWi2inp7GSe3__8)
- [ROB 101: Computational Linear Algebra - University of Michigan](https://github.com/michiganrobotics/rob101/tree/main/Fall%202021) ([Youtube - Fall 2021](https://www.youtube.com/playlist?list=PLdPQZLMHRjDJ5d_dE4FeOviv0gRe4UYsB))
- [ROB 101: Computational Linear Algebra - University of Michigan](https://github.com/michiganrobotics/rob101/tree/main/Fall%202021) ([Youtube - Fall 2021](https://www.youtube.com/playlist?list=PLdPQZLMHRjDJ5d_dE4FeOviv0gRe4UYsB))
- [ROB 102: Introduction to AI and Programming - University of Michigan](https://robotics102.github.io/)
- [ROB 102: Introduction to AI and Programming - University of Michigan](https://robotics102.github.io/)