└── README.md /README.md: -------------------------------------------------------------------------------- 1 | ## Computer Science Roadmap (AI Track) 2 | 3 | - [x] [Learning How to Learn](https://www.coursera.org/learn/learning-how-to-learn) 4 | 5 | ### Intro to CS 6 | 7 | - [x] [CS50 - Introduction to Computer Science - Harvard](cs50.tv/) 8 | - [x] [6.0001 - Introduction to Computer Science and Programming in Python, Fall 2016 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/) 9 | - [x] [6.0002 - Introduction to Computational Thinking and Data Science, Fall 2016 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/) 10 | 11 | ### Programming 12 | 13 | - [x] [CS61A - Structure and Interpretation of Computer Programs (Python + Scheme) - UC Berkeley](http://cs61a.org/) 14 | - [ ] [CS61A - Structure and Interpretation of Computer Programs (Scheme), 2010 - UC Berkeley](https://www.youtube.com/playlist?list=PLhMnuBfGeCDNgVzLPxF9o5UNKG1b-LFY9) 15 | - [x] [CS106A - Programming Methodology (Java) - Stanford](https://see.stanford.edu/Course/CS106A) 16 | - [ ] [CS106B - Programming Abstractions (C++) - Stanford](https://see.stanford.edu/Course/CS106B) 17 | - [ ] [CS107 - Programming Paradigms - Stanford](https://see.stanford.edu/Course/CS107) 18 | - [ ] [CSE341 - Programming Languages, Spring 2013 - University of Washington](https://courses.cs.washington.edu/courses/cse341/13sp/) 19 | - [ ] [CS212 - Design of Computer Programs - Peter Norvig](https://eu.udacity.com/course/design-of-computer-programs--cs212) 20 | - [ ] [CS210 - Functional Programming in Scala - EPFL](https://www.coursera.org/specializations/scala) 21 | - [ ] [6.S095 - Programming for the Puzzled, Spring 2018 - MIT](https://www.youtube.com/playlist?list=PLUl4u3cNGP62QumaaZtCCjkID-NgqrleA) 22 | 23 | ### Maths 24 | 25 | - **Calculus** 26 | - [x] [18.01 - Single Variable Calculus, Fall 2006 - MIT](https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/) 27 | - [x] [18.02 - Multivariable Calculus, Fall 2007 - MIT](https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/) 28 | - [ ] [18.03 - Differential Equations, Spring 2010 - MIT](https://ocw.mit.edu/courses/mathematics/18-03-differential-equations-spring-2010/) 29 | 30 | - **Linear Algebra** 31 | - [x] [18.06 - Linear Algebra, Fall 2011 - MIT](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/) 32 | - [ ] [Linear Algebra Review - CMU](http://www.cs.cmu.edu/~zkolter/course/linalg/index.html) 33 | - [ ] [Computational Linear Algebra](https://www.youtube.com/playlist?list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY) 34 | 35 | - **Probability and Statistics** 36 | - [x] [6.041 - Probabilistic Systems Analysis and Applied Probability, Fall 2013 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013/) 37 | - [ ] [STAT110 - Probability - Harvard](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo) 38 | - [ ] [18.650 - Statistics for Applications, Fall 2016 - MIT](https://ocw.mit.edu/courses/mathematics/18-650-statistics-for-applications-fall-2016/) 39 | - [ ] [36-705 - Intermediate Statistics, Fall 2016 - CMU](http://www.stat.cmu.edu/~larry/=stat705/) 40 | - [ ] [6.262 - Discrete Stochastic Processes, Spring 2011 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-262-discrete-stochastic-processes-spring-2011/) 41 | - [ ] [AM207 - Stochastic Methods for Data Analysis, Inference and Optimization, 2016 - Harvard](http://am207.github.io/2016/index.html) 42 | 43 | - **Discrete Maths** 44 | - [x] [6.042J - Mathematics for Computer Science, Fall 2010 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/) 45 | 46 | - **Opmitisation** 47 | - [ ] [EE364A - Convex Optimization I - Stanford](https://see.stanford.edu/Course/EE364A) 48 | - [ ] [EE364B - Convex Optimization II - Stanford](https://see.stanford.edu/Course/EE364B) 49 | - [ ] [10-725 - Convex Optimization, Fall 2016 - CMU](http://www.stat.cmu.edu/~ryantibs/convexopt/) 50 | - [ ] [10-801 - Advanced Optimization and Randomized Methods, Spring 2014 - CMU](http://www.cs.cmu.edu/~suvrit/teach/aopt.html) 51 | 52 | - **Maths for ML (mostly books)** 53 | - [ ] [10-606 - Math Background for Machine Learning, Fall 2017 - CMU](https://www.youtube.com/playlist?list=PL7y-1rk2cCsAqRtWoZ95z-GMcecVG5mzA) 54 | - [ ] [18-657 - Mathematics of Machine Learning, Fall 2015 - MIT](https://ocw.mit.edu/courses/mathematics/18-657-mathematics-of-machine-learning-fall-2015/) 55 | - [ ] [CO-496 - Mathematics for Inference and Machine Learning - Imperial College](http://wp.doc.ic.ac.uk/sml/teaching/mathematics-for-machine-learning-autumn-2016/) 56 | - [ ] [Book - Mathematics for Machine Learning - Imperial College](https://mml-book.com/) 57 | - [ ] [Book - Mathematics for Machine Learning - UC Berkeley](http://gwthomas.github.io/docs/math4ml.pdf) 58 | 59 | - **Other** 60 | - [ ] [MOOC - Introduction to Logic - Stanford](https://www.coursera.org/learn/logic-introduction/) 61 | - [ ] [18.S096 - Topics in Mathematics with Application in Finance, Fall 2013 - MIT](https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/) 62 | - [ ] [MOOC - Game Theory - Stanford](https://www.coursera.org/learn/game-theory-1) 63 | - [x] [MOOC - Discrete Optimization - University of Melbourne](https://www.coursera.org/learn/discrete-optimization) 64 | - [ ] [Operations Research - SUNY Binghamton University](https://www.youtube.com/playlist?list=PLgA4wLGrqI-ll9OSJmR5nU4lV4_aNTgKx) 65 | - [ ] [Linear Programming, Fall 2016 - Penn State University](https://www.youtube.com/playlist?list=PLbxFfU5GKZz1Tm_9RR5M_uvdOXpJJ8LC3) 66 | 67 | ### Data Structures and Algorithms 68 | 69 | - [x] [CS61B - Data Structures, Spring 2019 - UC Berkeley](https://sp19.datastructur.es/) 70 | - [ ] [6.006 - Introduction to Algorithms, Fall 2011 - MIT](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011/) 71 | - [ ] [COS226 - Algorithms - Princeton](https://algs4.cs.princeton.edu/home/) 72 | - [ ] [6.046J - Design and Analysis of Algorithms, Spring 2015 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2015/) 73 | - [ ] [CS161 - Algorithms: Design and Analysis, Part 1 - Stanford](https://lagunita.stanford.edu/courses/course-v1:Engineering+Algorithms1+SelfPaced/about) 74 | - [ ] [CS161 - Algorithms: Design and Analysis, Part 2 - Stanford](https://lagunita.stanford.edu/courses/course-v1:Engineering+Algorithms2+SelfPaced/about) 75 | - [ ] [6.851 - Advanced Data Structures, Spring 2012 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-851-advanced-data-structures-spring-2012/) 76 | - [ ] [CS224 - Advanced Algorithms, Fall 2014 - Harvard](http://people.seas.harvard.edu/~minilek/cs224/fall14/index.html) 77 | - [ ] [CS229R - Algorithms for Big Data, Fall 2015 - Harvard](http://people.seas.harvard.edu/~minilek/cs229r/fall15/index.html) 78 | - [ ] [CS170 - Efficient Algorithms and Intractable Problems, Fall 2020 - UC Berkeley](https://cs170.org/) 79 | 80 | ### Computer Architecture 81 | 82 | - [ ] [CS61C - Great Ideas in Computer Architecture, Spring 2015 - UC Berkeley](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iCl2-D-FS5mk0jFF6cYSJs_) 83 | - [ ] [CS152 - Computer Architecture and Engineering, Spring 2016 - UC Berkeley](https://www.youtube.com/playlist?list=PLkFD6_40KJIwEiwQx1dACXwh-2Fuo32qr) 84 | - [ ] [18-447 - Computer Architecture, Spring 2015 - CMU](http://www.archive.ece.cmu.edu/~ece447/s15/doku.php?id=schedule) 85 | - [ ] [15-418 - Parallel Computer Architecture and Programming, Spring 2016 - CMU](https://www.youtube.com/playlist?list=PLpIxOj-HnDsO4Atvrp86c-4La9Mq3kMQZ) 86 | - [ ] [CS267 - Applications of Parallel Computers, Spring 2016 - UC Berkeley](https://people.eecs.berkeley.edu/~demmel/cs267_Spr16/) 87 | 88 | ### System Programming 89 | 90 | - [ ] [15-213 - Introduction to Computer Systems, Fall 2015 - CMU](https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22b96d90ae-9871-4fae-91e2-b1627b43e25e%22) 91 | - [ ] [CS162 - Operating Systems and System Programming, Spring 2015 - UC Berkeley](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs162-spring2015-berkeley.html) 92 | - [ ] [6.824 - Distributed Systems, Spring 2020 - MIT](https://www.youtube.com/playlist?list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB) 93 | - [ ] [CS436 - Distributed Computer Systems, Winter 2012 - University of Waterloo](https://www.youtube.com/playlist?list=PLawkBQ15NDEkDJ5IyLIJUTZ1rRM9YQq6N) 94 | 95 | ### Software Engineering 96 | 97 | - [ ] [CS169 - Software Engineering, Spring 2015 - UC Berkeley](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs169-spring2015-berkeley.html) 98 | - [ ] [CS6310 - Software Architecture & Design - Georgia Tech](https://eu.udacity.com/course/software-architecture-design--ud821) 99 | - [ ] [CS5150 - Software Engineering, Fall 2014 - Cornell](http://www.cs.cornell.edu/courses/cs5150/2014fa/materials.html) 100 | - [ ] [CS164 - Software Engineering, Spring 2014 - Harvard](http://cs164.tv/2014/spring/) 101 | 102 | ### Database Systems 103 | 104 | - [x] [CS145 - Introduction to Databases - Stanford](https://lagunita.stanford.edu/courses/Home/Databases/Engineering/about) 105 | - [ ] [CS186 - Introduction to Database Systems, Spring 2015 - UC Berkeley](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iBVK2QzAV-R7NMA1ZkaiR2y) 106 | - [ ] [15-445 - Introduction to Database Systems, Fall 2017 - CMU](https://15445.courses.cs.cmu.edu/fall2017/) 107 | - [ ] [15-721 - Advanced Database Systems, Spring 2018 - CMU](https://15721.courses.cs.cmu.edu/spring2018/) 108 | 109 | ### Computer Networks 110 | 111 | - [ ] [14-740 - Fundamentals of Computer Networks, Fall 2017 - CMU](http://www.ini740.com/F17/index.html) 112 | - [ ] [CS144 - Introduction to Computer Networking - Stanford](https://lagunita.stanford.edu/courses/Engineering/Networking-SP/SelfPaced/about) 113 | 114 | ### Compilers 115 | 116 | - [ ] [CS143 - Compilers, Fall 2014 - Stanford](https://lagunita.stanford.edu/courses/Engineering/Compilers/Fall2014/about) 117 | - [ ] [CS164 - Programming Languages and Compilers, Spring 2012 - UC Berkeley](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs164-spring2012-berkeley.html) 118 | 119 | ### Theoretical CS 120 | 121 | - [ ] [15-251 - Great Ideas in Theoretical Computer Science - CMU](https://www.youtube.com/playlist?list=PLm3J0oaFux3aafQm568blS9blxtA_EWQv) 122 | - [ ] [CS154 - Automata Theory - Stanford](https://lagunita.stanford.edu/courses/course-v1:ComputerScience+Automata+SelfPaced/about) 123 | - [ ] [Category Theory, Summer 2016](https://www.youtube.com/playlist?list=PLbgaMIhjbmEnaH_LTkxLI7FMa2HsnawM_) 124 | 125 | ### Machine Learning and Artificial Intelligence 126 | 127 | - **Artificial Intelligence** 128 | - [ ] [CS188 - Introduction to Artificial Intelligence, Fall 2018 - UC Berkeley](https://inst.eecs.berkeley.edu/~cs188/fa18/) 129 | - [ ] [6.034 - Artificial Intelligence, Fall 2010 - MIT](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/) 130 | - [ ] [15-780 - Graduate Artificial Intelligence, Spring 2017 - CMU](https://www.youtube.com/playlist?list=PLpIxOj-HnDsPfw9slkk0BfwuiNEYVnsd_) 131 | - [ ] [CS221 - Artificial Intelligence: Principles and Techniques, Fall 2019](https://www.youtube.com/playlist?list=PLoROMvodv4rO1NB9TD4iUZ3qghGEGtqNX) 132 | 133 | - **Machine Learning** 134 | - [ ] [STATS216 - Statistical Learning, Winter 2016 - Stanford](https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about) 135 | - [x] [CS229 - Machine Learning - Stanford](https://see.stanford.edu/course/cs229) 136 | - [ ] [CS155 - Machine Learning & Data Mining, Winter 2017 - Caltech](http://www.yisongyue.com/courses/cs155/2017_winter/) 137 | - [ ] [CS156 - Learning from Data, Caltech](https://work.caltech.edu/lectures.html) 138 | - [ ] [10-601 - Introduction to Machine Learning (MS), Spring 2015 - CMU](http://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml) 139 | - [ ] [10-701 - Introduction to Machine Learning (PhD), Spring 2011 - CMU](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) 140 | - [ ] [10-702 - Statistical Machine Learning, Spring 2015 - CMU](https://www.youtube.com/playlist?list=PLjbUi5mgii6BWEUZf7He6nowWvGne_Y8r) 141 | - [ ] [Information Theory, Pattern Recognition, and Neural Networks, 2012 - Cambridge](http://www.inference.org.uk/itprnn/) 142 | - [ ] [CS189/281A - Introduction to Machine Learning, Spring 2016 - UC Berkeley](https://people.eecs.berkeley.edu/~jrs/189s16/) 143 | - [ ] [C281B - Scalable Machine Learning, 2012 - UC Berkeley](http://alex.smola.org/teaching/berkeley2012/syllabus.html) 144 | - [ ] [STA4273H - Large Scale Machine Learning, Winter 2015 - University of Toronto](http://www.cs.toronto.edu/~rsalakhu/STA4273_2015/lectures.html) 145 | - [ ] [18.409 - Algorithmic Aspects of Machine Learning, Spring 2015 - MIT](https://www.youtube.com/playlist?list=PLB3sDpSRdrOvI1hYXNsa6Lety7K8FhPpx) 146 | - [ ] [9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT](https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O) 147 | - [ ] [CPSC530 - Undergraduate Machine Learning, 2012 - University of British Columbia](https://www.youtube.com/playlist?list=PLE6Wd9FR--Ecf_5nCbnSQMHqORpiChfJf) 148 | - [ ] [CPSC540 - Graduate Machine Learning, 2013 - University of British Columbia](https://www.cs.ubc.ca/~nando/540-2013/lectures.html) 149 | 150 | - **Deep Learning** 151 | - [ ] [CS230 - Deep Learning, Fall 2018 - Stanford](http://cs230.stanford.edu/) 152 | - [ ] [6.S191 - Introduction to Deep Learning - MIT](http://introtodeeplearning.com/) 153 | - [ ] [Machine Learning, Fall 2014 - University of Oxford](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) 154 | - [ ] [CSC321 - Neural Networks for Machine Learning - University of Toronto](https://www.coursera.org/learn/neural-networks) 155 | - [ ] [MOOC - Deep Learning Specialisation- deeplearning.ai](https://www.coursera.org/specializations/deep-learning) 156 | - [x] [CS231N - Convolutional Neural Networks for Visual Recognition, Spring 2017 - Stanford](http://cs231n.stanford.edu/2017/) 157 | - [x] [CS224N - Natural Language Processing with Deep Learning, Winter 2019 - Stanford](https://www.youtube.com/playlist?list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z) 158 | - [ ] [CS224U - Natural Language Understanding, Spring 2019 - Stanford](https://www.youtube.com/playlist?list=PLoROMvodv4rObpMCir6rNNUlFAn56Js20) 159 | - [ ] [Deep Learning for Natural Language Processing - Oxford](https://github.com/oxford-cs-deepnlp-2017/lectures) 160 | - [ ] [6.S094 - Deep Learning for Self-Driving Cars - MIT](https://selfdrivingcars.mit.edu/) 161 | - [ ] [CS294-129 - Designing, Visualizing and Understanding Deep Neural Networks, Fall 2016 - UC Berkeley](https://www.youtube.com/playlist?list=PLkFD6_40KJIxopmdJF_CLNqG3QuDFHQUm) 162 | - [ ] [CS330 - Deep Multi-Task Learning and Meta Learning, Winter 2019 - Stanford](https://www.youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5) 163 | - [ ] [CS294-158 - Deep Unsupervised Learning, Spring 2020 - UC Berkeley](https://www.youtube.com/playlist?list=PLwRJQ4m4UJjPiJP3691u-qWwPGVKzSlNP) 164 | 165 | - **Reinforcement Learning** 166 | - [ ] [CS294 - Deep Reinforcement Learning, Fall 2018 - UC Berkeley](http://rail.eecs.berkeley.edu/deeprlcourse/) 167 | - [ ] [COMPM050 - Reinforcement Learning, 2015 - UCL](http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching.html) 168 | - [ ] [CS885 - Reinforcement Learning, Spring 2018 - University of Waterloo](https://cs.uwaterloo.ca/~ppoupart/teaching/cs885-spring18/index.html) 169 | - [ ] [Advanced Deep Learning & Reinforcement Learning - DeepMind & UCL](https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) 170 | - [ ] [CS294-112 - Deep Reinforcement Learning, Fall 2018 - UC Berkeley](https://www.youtube.com/playlist?list=PLkFD6_40KJIxJMR-j5A1mkxK26gh_qg37) 171 | - [ ] [CS234 - Reinforcement Learning, Winter 2019 - Stanford](https://www.youtube.com/playlist?list=PLoROMvodv4rOSOPzutgyCTapiGlY2Nd8u) 172 | 173 | - **Probabilistic Graphical Models** 174 | - [ ] [10-708 - Probabilistic Graphical Models, Spring 2014 - CMU](http://www.cs.cmu.edu/~epxing/Class/10708-14/lecture.html) 175 | - [ ] [CS228 - Probabilistic Graphical Models - Stanford](http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=ProbabilisticGraphicalModels) 176 | 177 | - **Miscs** 178 | - [ ] [CS246 - Mining of Massive Datasets - Stanford](https://lagunita.stanford.edu/courses/course-v1:ComputerScience+MMDS+SelfPaced/about) 179 | - [ ] [MOOC - Data Mining - University of Illinois](https://www.coursera.org/specializations/data-mining) 180 | - [ ] [MOOC - Recommender Systems - University of Minnesota](https://www.coursera.org/specializations/recommender-systems) 181 | - [ ] [Information Retrival, Fall 2017 - University of Freiburg](https://ad-wiki.informatik.uni-freiburg.de/teaching/InformationRetrievalWS1718) 182 | - [ ] [Information Retrieval and Web Search Engines, Winter 2015 - Technische Universität Braunschweig](http://www.ifis.cs.tu-bs.de/teaching/ws-1516/IRWS) 183 | - [ ] [CS224W - Machine Learning with Graphs, Fall 2019 - Stanford](https://www.youtube.com/playlist?list=PLUjDWbHzLn6NOha7_RnC5LOXurenpy-QE) 184 | - [ ] [CS520 - Knowledge Graphs Seminar, Spring 2020 - Stanford](https://www.youtube.com/playlist?list=PLDhh0lALedc7LC_5wpi5gDnPRnu1GSyRG) 185 | --------------------------------------------------------------------------------