Added omit-in-toc, and Grammar Corrected (#298)

Added Omit in TOC comments in readme for contributors, Grammar Corrected, and Few Courses Added. Also Many Issues solved
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# Contribution Guidelines
- 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.
- Recently the 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 links 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 a 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.

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# Notes
- 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>.
- Intent of this list is to act as Online bookmarks/lookup table for freely available online video courses. The focus would be to keep the list concise so that it is easy to browse. It would be easier to skim through a 15-page list, find the course and start learning than having to read 60 pages of t&ltext. If you are a student or from non-CS background, please try a few courses to decide for yourself which course suits your learning curve best.
- 90% of courses on Data Structures/Algorithms/Operating Systems/Machine Learning/Computer Networks/etc tend to have 80-90% overlap in the 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 the syllabus/notes/assignments, please visit the link to the course or use Google search with the course number/name. If a course has excellent notes/assignments/projects which cannot be reached through the video's link, please feel free to add links alongside.
- If available, please add the 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.
- [MIT Curriculum Guide](https://ocw.mit.edu/courses/mit-curriculum-guide/)
- [MIT New (Fall 2016) Degree Requirements](https://www.eecs.mit.edu/curriculum2016)
- [Stanford Current CS Program Sheets](http://csmajor.stanford.edu/ProgramSheets.shtml)
- [UMN Computer Science Course Prerequisite Chart](https://www.cs.umn.edu/sites/cs.umn.edu/files/cseprerequisite_chart.pdf)
- Disclaimer: The links have been taken from public domain websites like Open courseware sites, class-central, , YouTube channels for Universities, University pages, Google, itunes U, blog posts and similar sites like awesome-courses etc. If you are University Professor for any course listed below and would like Your course to be removed from the list, please raise an issue with course details.
- If you need assistance in deciding the order in which courses should be taken, please refer to sample Course prerequisite charts by Universities to familiarize yourself with the standard CS curriculum. If you need to know the prerequisites for a particular course not covered by the below samples, please check the course link or try Google.
- [MIT EECS Curriculum](https://www.eecs.mit.edu/academics/undergraduate-programs/curriculum/)
- [Stanford Program Sheets](https://cs.stanford.edu/degrees/ug/ProgramSheets.shtml)
- [Stanford Course and Requirement Overview](https://cs.stanford.edu/degrees/ug/Requirements.shtml)
- [UMN Computer Science Course Prerequisite Chart](https://onestop.umn.edu/registration/register-classes/course-prerequisites)
- Disclaimer: The links have been taken from public domain websites like Open courseware sites, class-central, YouTube channels for Universities, University pages, Google, itunes U, blog posts, and similar sites like awesome-courses, etc. If you are University Professor for any course listed below and would like Your course to be removed from the list, please raise an issue with course details.

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<!-- omit in toc -->
# Computer Science courses with video lectures
<!-- omit in toc -->
## Introduction
- Please check [NOTES](https://github.com/Developer-Y/cs-video-courses/blob/master/NOTES.md) for general information about this list.
- Please refer [CONTRIBUTING.md](https://github.com/Developer-Y/cs-video-courses/blob/master/CONTRIBUTING.md) for contribution guidelines.
- Please feel free to raise any genuine issue you may have, however it has been noticed that few people open empty issues to raise their github contribution on their account. Such spammers will be blocked.
- You are welcome to contribute, please create PR for actual college/University level courses. Please do not add links for small MOOCs, basic tutorials or advertisement for some sites/channels.
- Please feel free to raise any genuine issue you may have, however, it has been noticed that few people open empty issues to raise their GitHub contribution on their account. Such spammers will be blocked.
- You are welcome to contribute, please create PR for actual college/University level courses. Please do not add links for small MOOCs, basic tutorials, or advertisements for some sites/channels.
------------------------------
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- [Software Engineering](#software-engineering)
- [Artificial Intelligence](#artificial-intelligence)
- [Machine Learning](#machine-learning)
- [Web Programming and Internet Technologies](#web-programming-and-internet-technologies)
- [Computer Networks](#computer-networks)
- [Math for Computer Scientist](#math-for-computer-scientist)
- [Web Programming and Internet Technologies](#web-programming-and-internet-technologies)
- [Theoretical CS and Programming Languages](#theoretical-cs-and-programming-languages)
- [Embedded Systems](#embedded-systems)
- [Real time system evaluation](#real-time-system-evaluation)
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- [Blockchain Development](#blockchain-development)
- [Misc](#misc)
<!-- omit in toc -->
## Courses
------------------------------
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- [CIS 522 - Deep Learning - U Penn](https://www.youtube.com/@cis522-deeplearning8/playlists)
- [UVA DEEP LEARNING COURSE](http://uvadlc.github.io/#lecture)
- [Deep Learning (Fall 2020) - Georgia Tech](https://www.youtube.com/playlist?list=PL-fZD610i7yB7gDnPDpFcKpHI9X8z3OQ7)
- [CS7015 - Deep Learning - Prof. Mitesh M. Khapra - IIT Madras](https://www.youtube.com/playlist?list=PLyqSpQzTE6M9gCgajvQbc68Hk_JKGBAYT)
- **Reinforcement Learning**
- [CS234: Reinforcement Learning - Winter 2019 - Stanford University](https://www.youtube.com/playlist?list=PLoROMvodv4rOSOPzutgyCTapiGlY2Nd8u)
- [Introduction to reinforcement learning - UCL](https://www.youtube.com/playlist?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ)
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- [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))
- **Natural Language Processing**
- [CS 224N - Deep Learning for Natural Language Processing, Stanford University](http://web.stanford.edu/class/cs224n/) ([Lectures - Youtube](https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ))
- [CS 224N -Natural Language Processing with Deep Learning - Stanford University](http://web.stanford.edu/class/cs224n/) ([Lectures - Winter 2019](https://youtube.com/playlist?list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z)) ([Lectures - Winter 2021](https://youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ))
- [CS 224N - Natural Language Processing, Stanford University](https://web.stanford.edu/~jurafsky/NLPCourseraSlides.html) ([Lecture videos](https://academictorrents.com/details/d2c8f8f1651740520b7dfab23438d89bc8c0c0ab))
- [CS 124 - From Languages to Information - Stanford University](https://www.youtube.com/channel/UC_48v322owNVtORXuMeRmpA/playlists?view=50&sort=dd&shelf_id=2)
- [fast.ai Code-First Intro to Natural Language Processing](https://www.youtube.com/playlist?list=PLtmWHNX-gukKocXQOkQjuVxglSDYWsSh9) ([Github](https://github.com/fastai/course-nlp))
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### Computer Networks
- [14-740 - Fundamentals of Computer Networks - CMU](http://www.ini740.com/)
- [14-740 - Fundamentals of Computer Networks - CMU](https://www.andrew.cmu.edu/course/14-740-s18/index/lecture_index.html)
- [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))
- [Audio/Video Recordings and Podcasts of Professor Raj Jain's Lectures - Washington University in St. Louis](http://www.cse.wustl.edu/~jain/videos.htm) ([YouTube](https://www.youtube.com/user/ProfRajJain/playlists))
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- [Computer Science 70, 001 - Spring 2015](https://www.youtube.com/playlist?list=-XXv-cvA_iD8wQm8U0gG_Z1uHjImKXFy)
- [CSE 547 Discrete Mathematics, Prof Skiena, University of Stony Brook](http://www3.cs.stonybrook.edu/~algorith/math-video/)
- [Discrete Structures (Summer 2011) - Rutgers, The State University of New Jersey](https://itunes.apple.com/us/course/discrete-structures-summer/id698728837)
- [Discrete Mathematics and Mathematical Reasoning 2015/16 - University of Edinburgh](http://groups.inf.ed.ac.uk/vision/VIDEO/2015/dmmr.htm)
- [Discrete Mathematics and Mathematical Reasoning 2015/16 - University of Edinburgh](https://www.inf.ed.ac.uk/teaching/courses/dmmr/)
- [Discrete Mathematical Structures - IIT Madras](https://nptel.ac.in/courses/106106094/)
- [Discrete Structures - Pepperdine University](https://itunes.apple.com/us/course/discrete-structures/id546468789)
- **Probability & Statistics**
@ -602,6 +606,7 @@ Table of Contents
- [Statistical Computing for Scientists and Engineers - Notre Dame](https://www.youtube.com/playlist?list=PLd-PuDzW85AeltIRcjDY7Z4q49NEAuMcA)
- [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)
- [Essential Mathematics for Machine Learningv- July 2018 - IIT Roorkee - YouTube Lectures](https://www.youtube.com/playlist?list=PLLy_2iUCG87D1CXFxE-SxCFZUiJzQ3IvE)
- [Numerics of Machine Learning (Winter 2022/23) - Tübingen Machine Learning](https://www.youtube.com/playlist?list=PL05umP7R6ij2lwDdj7IkuHoP9vHlEcH0s)
------------------------------
@ -682,18 +687,15 @@ Table of Contents
- [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)
- [CS149 Introduction to Embedded Systems - Spring 2011 - UCBerkeley](https://youtube.com/playlist?list=PLu0nzW8Es1x0RIvuWdw1Diez2Clk8xAX5)
- [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 University of Potsdam](https://www.tele-task.de/series/864/)
- [Embedded Software Testing - IIT Madras](https://nptel.ac.in/courses/117106112/)
- [Embedded Systems - IIT Delhi](https://nptel.ac.in/courses/108102045/)
@ -703,7 +705,6 @@ Table of Contents
- [EE260 Embedded Systems by Robert Paz](https://www.youtube.com/playlist?list=PLnvE9iJk1wvib_pdUPdQGYZrkrmg9mf__)
- [IoT Summer School](https://www.youtube.com/playlist?list=PLHih6DnKQaoYQ5PIT3Tp-UrqUguDYWYQu)
- [ECSE 421 - Embedded Systems - McGill](http://www.cim.mcgill.ca/~jer/courses/es/)
- [EE402 - Object-oriented Programming with Embedded Systems](http://ee402.eeng.dcu.ie/lecture-videos)
- [NOC:Advanced IOT Applications - IISc Bangalore](https://nptel.ac.in/courses/108/108/108108123/)
- [NOC:Design for internet of things - IISc Bangalore](https://nptel.ac.in/courses/108/108/108108098/)
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### Image Processing and Computer Vision
- [MOOC - Digital Image processing - Duke/Coursera](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A79y1StvUUqgyL-O0fZh2rs)
- [Computer Vision 2011 - EPFL, Switzerland](http://www.klewel.com/conferences/epfl-computer-vision/)
- [Digital Image Processing - IIT Kharagpur](https://nptel.ac.in/courses/117105079/)
- [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))
@ -1006,7 +1006,7 @@ Pricing Theory I / Applied Probability for Mathematical Finance - University of
- [Blockchain, Solidity, and Full Stack Web3 Development with JavaScript](https://youtu.be/gyMwXuJrbJQ)
- [Blockchain Fundamentals Decal 2018 - Berkeley DeCal](https://www.youtube.com/playlist?list=PLSONl1AVlZNU0QTGpbgEQXKHcmgYz-ddT)
- [Blockchain for Developers Decal - Spring 2018 - Berkeley DeCal](https://www.youtube.com/playlist?list=PLSONl1AVlZNUzp71_H1kb87PvIh8kIZU9)
- [Cryptocurrency Engineering and Design - Spring 2018 - MIT](https://ocw.mit.edu/courses/media-arts-and-sciences/mas-s62-cryptocurrency-engineering-and-design-spring-2018/lecture-videos/)
- [Cryptocurrency Engineering and Design - Spring 2018 - MIT](https://ocw.mit.edu/courses/mas-s62-cryptocurrency-engineering-and-design-spring-2018/video_galleries/lecture-videos/)
- [15.S12 Blockchain and Money, Fall 2018 - MIT](https://www.youtube.com/playlist?list=PLUl4u3cNGP63UUkfL0onkxF6MYgVa04Fn)
- [Blockchain - Foundations and Use Cases](https://www.coursera.org/learn/blockchain-foundations-and-use-cases/home/welcome)
- **Become Blockchain Developer**