Хабр, привет. Перевел пост, который идёт строго (!) в закладки и передаётся коллегам. Он со списком видеолекций, которые будут полезны в 2024 году. Все видео на ютуб и удобных платформах, изучать, в том числе, просто на фоне — бесценно. Они будут полезны как для расширения кругозора, так и уже опытным специалистам.
Меня зовут Рушан, и я автор Telegram‑канала Нейрон. Отмечу, что если среди читателей есть желающие помочь, и добавить дополнительный материал в статью, пожалуйста, свяжитесь со мной. Я промодерирую и добавлю в список.
Итак, давайте начнём изучение списка.
Курсы
Введение в информатику
CS 10 - The Beauty and Joy of Computing - Spring 2015 - Dan Garcia - UC Berkeley InfoCoBuild
6.0001 - Introduction to Computer Science and Programming in Python - MIT OCW
6.001 - Structure and Interpretation of Computer Programs, MIT
Introduction to Computational Thinking - MIT
CS 50 - Introduction to Computer Science, Harvard University (cs50.tv)
CS 61A - Structure and Interpretation of Computer Programs [Python], UC Berkeley
CPSC 110 - Systematic Program Design [Racket], University of British Columbia
CS50's Understanding Technology
CSE 142 Computer Programming I (Java Programming), Spring 2016 - University of Washington
CS 1301 Intro to computing - Gatech
CS 106A - Programming Methodology, Stanford University (Lecture Videos)
CS 106B - Programming Abstractions, Stanford University (Lecture Videos)
CS 106L - Standard C++ Programming(Lecture Videos)
CS 106X - Programming Abstractions in C++ (Lecture Videos)
CS 107 - Programming Paradigms, Stanford University
CmSc 150 - Introduction to Programming with Arcade Games, Simpson College
LINFO 1104 - Paradigms of computer programming, Peter Van Roy, Université catholique de Louvain, Belgium - EdX
FP 101x - Introduction to Functional Programming, TU Delft
Introduction to Problem Solving and Programming - IIT Kanpur
Introduction to programming in C - IIT Kanpur
Programming in C++ - IIT Kharagpur
Python Boot Camp Fall 2016 - Berkeley Institute for Data Science (BIDS)
CS 101 - Introduction to Computer Science - Udacity
6.00SC - Introduction to Computer Science and Programming (Spring 2011) - MIT OCW
6.00 - Introduction to Computer Science and Programming (Fall 2008) - MIT OCW
6.01SC - Introduction to Electrical Engineering and Computer Science I - MIT OCW
Modern C++ Course (2018) - Bonn University
Modern C++ (Lecture & Tutorials, 2020, Vizzo & Stachniss) - University of Bonn
UW Madison CS 368 C++ for Java Programmers Fall 2020, by Michael Doescher
UW Madison CS 354 Machine Organization and Programming spring 2020, 2021, by Michael Doescher
Cornell ECE 4960 Computational and Software Engineering spring 2017, by Edwin Kan
Структуры данных и алгоритмы
ECS 36C - Data Structures and Algorithms (C++) - Spring 2020 - Joël Porquet-Lupine - UC Davis
Programming and Data Structures with Python, 2021-2022, Sem I - by Prof. Madhavan Mukund, CMI
6.006 - Introduction to Algorithms, MIT OCW
MIT 6.006 Introduction to Algorithms, Spring 2020
Algorithms: Design and Analysis 1 - Stanford University
Algorithms: Design and Analysis 2 - Stanford University
COS 226 Algorithms, Youtube, Princeton - by Robert Sedgewick and Kevin Wayne
CSE 331 Introduction to Algorithm Design and Analysis, SUNY University at Buffalo, NY - Fall 2017 (Lectures) (Homework Walkthroughs)
CSE 373 - Analysis of Algorithms, Stony Brook - Prof Skiena
COP 3530 Data Structures and Algorithms, Prof Sahni, UFL (Videos)
CS225 - Data Structures - University of Illinois at Urbana-Champaign(Video lectures)
CS2 - Data Structures and Algorithms - Richard Buckland - UNSW
Data Structures - Pepperdine University
CS 161 - Design and Analysis of Algorithms, Prof. Tim Roughgarden, Stanford University
6.046J - Introduction to Algorithms - Fall 2005, MIT OCW
Introduction to Algorithms (Spring 2020), MIT OCW
6.046 - Design and Analysis of Algorithms, Spring 2015 - MIT OCW
CS 473 - Algorithms - University of Illinois at Urbana-Champaign (Notes - Jeff Erickson) (YouTube)
COMP300E - Programming Challenges, Prof Skiena, Hong Kong University of Science and Technology - 2009
16s-4102 - Algorithms, University of Virginia (Youtube)
CS 61B - Data Structures (Java) - UC Berkeley(Youtube)
CS 170 Algorithms - UCBerkeley Fall 2018, Youtube Fall 2018,Bilibili 2013 Bilibili
ECS 122A - Algorithm Design and Analysis, UC Davis
CSEP 521 - Applied Algorithms, Winter 2013 - University of Washington (Videos)
Data Structures And Algorithms - IIT Delhi
Design and Analysis of Algorithms - IIT Bombay
Programming, Data Structures and Algorithms - IIT Madras
Design and Analysis of Algorithms - IIT Madras
Fundamental Algorithms:Design and Analysis - IIT Kharagpur
Programming and Data Structure - IIT Kharagpur
Programming, Data structures and Algorithms - IIT Madras
Programming, Data Structures and Algorithms in Python - IIT Madras
Programming and Data structures (PDS) - IIT Madras
COP 5536 Advanced Data Structures, Prof Sahni - UFL (Videos)
CS 261 - A Second Course in Algorithms, Stanford University (Youtube)
CS 224 - Advanced Algorithms, Harvard University (Lecture Videos) (Youtube)
CS 6150 - Advanced Algorithms (Fall 2016), University of Utah
CS 6150 - Advanced Algorithms (Fall 2017), University of Utah
ECS 222A - Graduate Level Algorithm Design and Analysis, UC Davis
6.851 - Advanced Data Structures, MIT (MIT OCW)
6.854 - Advanced Algorithms, MIT (Prof. Karger lectures)
CS264 Beyond Worst-Case Analysis, Fall 2014 - Tim Roughgarden Lecture (Youtube)
CS364A Algorithmic Game Theory, Fall 2013 - Tim Roughgarden Lectures
CS364B Advanced Mechanism Design, Winter 2014 - Tim Roughgarden Lectures
Algorithms - Aduni
6.889 - Algorithms for Planar Graphs and Beyond (Fall 2011) MIT
6.890 Algorithmic Lower Bounds: Fun with Hardness Proofs - MIT OCW
Computer Algorithms - 2 - IIT Kanpur
Parallel Algorithm - IIT Kanpur
Graph Theory - IISC Bangalore
Data Structures - mycodeschool
Algorithmic Game Theory, Winter 2020/21 - Uni Bonn
NETS 4120: Algorithmic Game Theory, Spring 2023 - UPenn
Introduction to Game Theory and Mechanism Design - IIT Kanpur
15-850 Advanced Algorithms - CMU Spring 2023
CS 270. Combinatorial Algorithms and Data Structures, Spring 2021 (Youtube)
CMU 15 850 Advanced Algorithms spring 2023, by Anupam Gupta
UC Berkeley CS 294-165 Sketching Algorithms fall 2020, by Jelani Nelson
UIUC CS 498 ABD / CS 598 CSC Algorithms for Big Data fall 2020, by Chandra Chekuri
Algorithms for Data Science spring 2021, by Anil Maheshwari
CMU 15 859 Algorithms for Big Data fall 2020, by David Woodruff
Системное программирование
15-213 Introduction to Computer Systems, Fall 2015 - CMU
CS361 - COMPUTER SYSTEMS - UIC
CS 3650 - Computer Systems - Fall 2020 - Nat Tuck - NEU (Lectures - YouTube)
CS 4400 – Computer Systems Fall 2016 - UoUtah
Systems - Aduni
CS110: Principles of Computer Systems - Stanford
Операционные системы
ECS 150 - Operating Systems and Systems Programming - Fall 2020 - Joël Porquet-Lupine - UC Davis
CS124 Operating Systems - California Institute of Technology, Fall 2018 - Youtube
CS 162 Operating Systems and Systems Programming, Spring 2015 - University of California, Berkeley
CS 4414 - Operating Systems, University of Virginia (rust-class)
CS 4414 Operating Systems, Fall 2018 - University of Virginia
CSE 421/521 - Introduction to Operating Systems, SUNY University at Buffalo, NY - Spring 2016 (Lectures - YouTube) (Recitations 2016) (Assignment walkthroughs)
CS 377 - Operating Systems, Fall 16 - Umass OS
6.828 - Operating System Engineering [Fall 2014]
6.S081 - Operating System Engineering [Fall 2020]
CSE 30341 - Operating Systems, Spr 2008
CSEP 551 Operating Systems Autumn 2014 - University of Washington
Introduction to Operating Systems - IIT Madras
CS194 Advanced Operating Systems Structures and Implementation, Spring 2013 InfoCoBuild, UC Berkeley
CSE 60641 - Graduate Operating Systems, Fall 08
Advanced Programming in the UNIX Environment
Distributed Systems
CS 677 - Distributed Operating Systems, Spring 16 - Umass OS
CS 436 - Distributed Computer Systems - U Waterloo
6.824 - Distributed Systems, Spring 2015 - MIT
6.824 Distributed Systems - Spring 2020 - MIT (Youtube)
Distributed Systems Lecture Series
Distributed Algorithms, https://canvas.instructure.com/courses/902299
CSEP 552 - PMP Distributed Systems, Spring 2013 - University of Washington (Videos)
CSE 490H - Scalable Systems: Design, Implementation and Use of Large Scale Clusters, Autumn 2008 - University of Washington (Videos)
MOOC - Cloud Computing Concepts - UIUC
Distributed Systems (Prof. Pallab Dasgupta)
EdX KTHx ID2203 Reliable Distributed Algorithms
Distributed Data Management - Technische Universität Braunschweig, Germany
Information Retrieval and Web Search Engines - Technische Universität Braunschweig, Germany
Middleware and Distributed Systems (WS 2009/10) - Dr. Martin von Löwis - HPI
CSE 138 - Distributed Systems - UC Santa Cruz, Spring 2020 (2021)
Распределенные системы
CPCS 663 - Real-Time Systems: Video Material - TAMU
Real Time Systems - IIT Kharagpur
6.172 Performance Engineering of Software Systems - MIT OCW
Performance Evaluation of Computer Systems - IIT Madras
Storage Systems - IISC Bangalore
MAP6264 - Queueing Theory - FAU(Video Lectures)
EE 380 Colloquium on Computer Systems - Stanford University (Lecture videos)
Системы баз данных
CMPSC 431W Database Management Systems, Fall 2015 - Penn State University Lectures - YouTube
CS121 - Introduction to Relational Database Systems, Fall 2016 - Caltech
CS 5530 - Database Systems, Spring 2016 - University of Utah
Distributed Data Management (WT 2018/19) - HPI University of Potsdam
MOOC - Database Stanford Dbclass
CSEP 544, Database Management Systems, Au 2015 - University of Washington
Database Design - IIT Madras
Fundamentals of Database Systems - IIT Kanpur
Principles of Database Management, Bart Baesens
FIT9003 Database Systems Design - Monash University
15-445 - Introduction to Database Systems, CMU (YouTube-2017, YouTube-2018, YouTube-2019, YouTube-2021, YouTube-2022)
15-721 - Database Systems, CMU (YouTube-2017, YouTube-2016)
15-721 Advanced Database Systems (Spring 2019) - CMU
CS122 - Relational Database System Implementation, Winter 2014-2015 - Caltech
CS 186 - Database Systems, UC Berkeley, Spring 2015 (Lectures- InfoCoBuild)
CS 6530 - Graduate-level Database Systems, Fall 2016, University of Utah (Lectures - YouTube)
6.830/6.814 - Database Systems [Fall 2014]
Informatics 1 - Data & Analysis 2014/15- University of Edinburgh
Database Management Systems, Aduni
D4M - Signal Processing on Databases
In-Memory Data Management (2013)Prof. Hasso Plattner - HPI
Distributed Data Management (WT 2019/20) - Dr. Thorsten Papenbrock - HPI
CS122d - NoSQL Data Management (Spring 21) - Prof. Mike Carey - UC Irvine
Разработка программного обеспечения
Объектно-ориентированный дизайн
ECE 462 Object-Oriented Programming using C++ and Java - Purdue
Object-oriented Program Design and Software Engineering - Aduni
OOSE - Object-Oriented Software Engineering, Dr. Tim Lethbridge
Object Oriented Systems Analysis and Design (Systems Analysis and Design in a Changing World)
CS 251 - Intermediate Software Design (C++ version) - Vanderbilt University
OOSE - Software Dev Using UML and Java
Object-Oriented Analysis and Design - IIT Kharagpur
CS3 - Design in Computing - Richard Buckland UNSW
Informatics 1 - Object-Oriented Programming 2014/15- University of Edinburgh
Software Engineering with Objects and Components 2015/16- University of Edinburgh
Разработка программного обеспечения
Computer Science 169- Software Engineering - Spring 2015 - UCBerkeley
Computer Science 169- Software Engineering - Fall 2019 - UCBerkeley
CS 5150 - Software Engineering, Fall 2014 - Cornell University
Introduction to Service Design and Engineering - University of Trento, Italy
CS 164 Software Engineering - Harvard
System Analysis and Design - IISC Bangalore
Software Engineering - IIT Bombay
Dependable Systems (SS 2014)- HPI University of Potsdam
Software Testing - IIT Kharagpur
Software Testing - Udacity, course-cs258 | 2015
Software Debugging - Udacity, course-cs259 | 2015
Software Engineering - Bauhaus-Uni Weimar
Архитектура программного обеспечения
CS 411 - Software Architecture Design - Bilkent University
MOOC - Software Architecture & Design - Udacity
Совпадения
CS176 - Multiprocessor Synchronization - Brown University (Videos from 2012)
CS 282 (2014): Concurrent Java Network Programming in Android
CSE P 506 – Concurrency, Spring 2011 - University of Washington (Videos)
CSEP 524 - Parallel Computation - University of Washington (Videos)
Parallel Programming Concepts (WT 2013/14) - HPI University of Potsdam
Parallel Programming Concepts (WT 2012/13) - HPI University of Potsdam
UIUC ECE 408 / CS 408 Applied Parallel Programming spring 2018, fall 2022, by Wen-mei Hwu, Sanjay Patel
UIUC ECE 508 / CS 508 Manycore Parallel Algorithms spring 2019, by Wen-mei Hwu
UIUC CS 420 / ECE 492 / CSE 402 Introduction to Parallel Programming for Scientists and Engineers fall 2015, by Sanjay Kale
Stanford CME 213 Introduction to Parallel Computing using MPI, openMP, and CUDA winter 2020, by Eric Darve
Разработка мобильных приложений
MOOC Programming Mobile Applications for Android Handheld Systems - University of Maryland
CS 193p - Developing Applications for iOS, Stanford University
CS S-76 Building Mobile Applications - Harvard
CS 251 (2015): Intermediate Software Design
Android App Development for Beginners Playlist - thenewboston
Android Application Development Tutorials - thenewboston
MOOC - Developing Android Apps - Udacity
MOOC - Advanced Android App Development - Udacity
CSSE490 Android Development Rose-Hulman Winter 2010-2011, Dave Fisher
iOS Course, Dave Fisher
Developing iPad Applications for Visualization and Insight - Carnegie Mellon University
Mobile Computing - IIT Madras
Mobile Information Systems - Bauhaus-Uni Weimar
Искусственный интеллект
CS50 - Introduction to Artificial Intelligence with Python (and Machine Learning), Harvard OCW
CS 188 - Introduction to Artificial Intelligence, UC Berkeley - Spring 2015
6.034 Artificial Intelligence, MIT OCW
CS221: Artificial Intelligence: Principles and Techniques - Autumn 2019 - Stanford University
15-780 - Graduate Artificial Intelligence, Spring 14, CMU
CSE 592 Applications of Artificial Intelligence, Winter 2003 - University of Washington
CS322 - Introduction to Artificial Intelligence, Winter 2012-13 - UBC (YouTube)
CS 4804: Introduction to Artificial Intelligence, Fall 2016
CS 5804: Introduction to Artificial Intelligence, Spring 2015
Artificial Intelligence - IIT Kharagpur
Artificial Intelligence - IIT Madras
Artificial Intelligence(Prof.P.Dasgupta) - IIT Kharagpur
MOOC - Intro to Artificial Intelligence - Udacity
MOOC - Artificial Intelligence for Robotics - Udacity
Graduate Course in Artificial Intelligence, Autumn 2012 - University of Washington
Agent-Based Systems 2015/16- University of Edinburgh
Informatics 2D - Reasoning and Agents 2014/15- University of Edinburgh
Artificial Intelligence - Hochschule Ravensburg-Weingarten
Deductive Databases and Knowledge-Based Systems - Technische Universität Braunschweig, Germany
Artificial Intelligence: Knowledge Representation and Reasoning - IIT Madras
Semantic Web Technologies by Dr. Harald Sack - HPI
Knowledge Engineering with Semantic Web Technologies by Dr. Harald Sack - HPI
T81-558: Applications of Deep Neural Networks by Jeff Heaton, 2022, Washington University in St. Louis
MSU programming for AI
Машинное обучение
Введение в машинное обучение
Introduction to Machine Learning for Coders
MOOC - Statistical Learning, Stanford University
Foundations of Machine Learning Boot Camp, Berkeley Simons Institute
CS155 - Machine Learning & Data Mining, 2017 - Caltech (Notes) (2016)
CS 156 - Learning from Data, Caltech
10-601 - Introduction to Machine Learning (MS) - Tom Mitchell - 2015, CMU (YouTube)
10-601 Machine Learning | CMU | Fall 2017
10-701 - Introduction to Machine Learning (PhD) - Tom Mitchell, Spring 2011, CMU (Fall 2014) (Spring 2015 by Alex Smola)
10 - 301/601 - Introduction to Machine Learning - Spring 2020 - CMU
10 - 301/601 - Introduction to Machine Learning - Fall 2023 - CMU
6.036 - Machine Learning, Broderick - MIT Fall 2020
Mediterranean Machine Learning summer school 2023
Applied Machine Learning (Cornell Tech CS 5787, Fall 2020)
Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati) (Spring 2022)
CMS 165 Foundations of Machine Learning and Statistical Inference - 2020 - Caltech
Microsoft Research - Machine Learning Course
CS 446 - Machine Learning, Fall 2016, UIUC
undergraduate machine learning at UBC 2012, Nando de Freitas
CS 229 - Machine Learning - Stanford University (Autumn 2018)
CS 189/289A Introduction to Machine Learning, Prof Jonathan Shewchuk - UCBerkeley
CPSC 340: Machine Learning and Data Mining (2018) - UBC
CS4780/5780 Machine Learning, Fall 2013 - Cornell University
CS4780/5780 Machine Learning, Fall 2018 - Cornell University (Youtube)
CSE474/574 Introduction to Machine Learning - SUNY University at Buffalo
CS 5350/6350 - Machine Learning, Fall 2016, University of Utah
ECE 5984 Introduction to Machine Learning, Spring 2015 - Virginia Tech
CSx824/ECEx242 Machine Learning, Bert Huang, Fall 2015 - Virginia Tech
STA 4273H - Large Scale Machine Learning, Winter 2015 - University of Toronto
CS 485/685 Machine Learning, Shai Ben-David, University of Waterloo
STAT 441/841 Classification Winter 2017 , Waterloo
10-605 - Machine Learning with Large Datasets, Fall 2016 - CMU
Information Theory, Pattern Recognition, and Neural Networks - University of Cambridge
Python and machine learning - Stanford Crowd Course Initiative
MOOC - Machine Learning Part 1a - Udacity/Georgia Tech (Part 1b Part 2 Part 3)
Machine Learning and Pattern Recognition 2015/16- University of Edinburgh
Introductory Applied Machine Learning 2015/16- University of Edinburgh
Pattern Recognition Class (2012)- Universität Heidelberg
Introduction to Machine Learning and Pattern Recognition - CBCSL OSU
Introduction to Machine Learning - IIT Kharagpur
Introduction to Machine Learning - IIT Madras
Pattern Recognition - IISC Bangalore
Pattern Recognition and Application - IIT Kharagpur
Pattern Recognition - IIT Madras
Machine Learning Summer School 2013 - Max Planck Institute for Intelligent Systems Tübingen
Machine Learning - Professor Kogan (Spring 2016) - Rutgers
CS273a: Introduction to Machine Learning (YouTube)
Machine Learning Crash Course 2015
COM4509/COM6509 Machine Learning and Adaptive Intelligence 2015-16
10715 Advanced Introduction to Machine Learning
Introduction to Machine Learning - Spring 2018 - ETH Zurich
Machine Learning - Pedro Domingos- University of Washington
Advanced Machine Learning - 2019 - ETH Zürich
Machine Learning (COMP09012)
Probabilistic Machine Learning 2020 - University of Tübingen
Statistical Machine Learning 2020 - Ulrike von Luxburg - University of Tübingen
COMS W4995 - Applied Machine Learning - Spring 2020 - Columbia University
Machine Learning for Engineers 2022 (YouTube)
10-418 / 10-618 (Fall 2019) Machine Learning for Structured Data
ORIE 4741/5741: Learning with Big Messy Data - Cornell
Machine Learning in IoT
Stanford CS229M: Machine Learning Theory - Fall 2021
Intro to Machine Learning and Statistical Pattern Classification - Prof Sebastian Raschka
CMU's Multimodal Machine Learning course (11-777), Fall 2020
EE104: Introduction to Machine Learning - Stanford University
CPSC 330: Applied Machine Learning (2020) - UBC
Machine Learning 2013 - Nando de Freitas, UBC
Machine Learning, 2014-2015, University of Oxford
10-702/36-702 - Statistical Machine Learning - Larry Wasserman, Spring 2016, CMU (Spring 2015)
10-715 Advanced Introduction to Machine Learning - CMU (YouTube)
CS 281B - Scalable Machine Learning, Alex Smola, UC Berkeley
100 Days of Machine Learning - CampusX (Hindi)
CampusX Data Science Mentorship Program 2022-23 (Hindi)
Statistical Machine Learning - S2023 - Benyamin Ghojogh
MIT 6.5940 EfficientML.ai Lecture, Fall 2023
TinyML - Tiny Machine Learning at UPenn
Machine Learning Hardware and Systems (Cornell Tech, Spring 2022)
ECE 4760 (Digital Systems Design Using Microcontrollers) at Cornell for the Fall, 2022
EfficientML.ai Lecture, Fall 2023, MIT 6.5940
CS189 Machine Learning 2022 - UCB
ETH Zurich Statistical Learning Theory spring 2021, by Joachim M. Buhmann
SFU CMPT 727 Statistical Machine Learning spring 2022, 2023, by Maxwell Libbrecht
UC Berkeley CS 189 / 289A Introduction to Machine Learning fall 2023, by Jennifer Listgarten & Jitendra Malik
UC Berkeley CS 189 / 289A Introduction to Machine Learning spring 2022, by Jonathan Shewchuk
UC Berkeley CS 189 Introduction to Machine Learning (CDSS offering) spring 2022, by Marvin Zhang
MIT 6.036 Introduction to Machine Learning spring 2019, by Leslie Kaelbling
UCLA STAT C161 Introduction to Pattern Recognition and Machine Learning winter 2023, by Arash Amini
UT Austin Machine Learning Algorithms & Statistical Learning by Adam Klivans & Qiang Liu
MSU Machine Learning
Анализ данных
CSEP 546, Data Mining - Pedro Domingos, Sp 2016 - University of Washington (YouTube)
CS 5140/6140 - Data Mining, Spring 2016, University of Utah (Youtube)
CS 5955/6955 - Data Mining, University of Utah (YouTube)
Statistics 202 - Statistical Aspects of Data Mining, Summer 2007 - Google (YouTube)
MOOC - Text Mining and Analytics by ChengXiang Zhai
Information Retrieval SS 2014, iTunes - HPI
MOOC - Data Mining with Weka
CS 290 DataMining Lectures
CS246 - Mining Massive Data Sets, Winter 2016, Stanford University (YouTube)
Data Mining: Learning From Large Datasets - Fall 2017 - ETH Zurich
Information Retrieval - Spring 2018 - ETH Zurich
CAP6673 - Data Mining and Machine Learning - FAU(Video lectures)
Data Warehousing and Data Mining Techniques - Technische Universität Braunschweig, Germany
Наука о данных
Data 8: The Foundations of Data Science - UC Berkeley (Summer 17)
CSE519 - Data Science Fall 2016 - Skiena, SBU
CS 109 Data Science, Harvard University (YouTube)
6.0002 Introduction to Computational Thinking and Data Science - MIT OCW
Data 100 - Summer 19- UC Berkeley
Distributed Data Analytics (WT 2017/18) - HPI University of Potsdam
Statistics 133 - Concepts in Computing with Data, Fall 2013 - UC Berkeley
Data Profiling and Data Cleansing (WS 2014/15) - HPI University of Potsdam
CS 229r - Algorithms for Big Data, Harvard University (Youtube)
Algorithms for Big Data - IIT Madras
Python Data Science with the TCLab (YouTube)
Вероятностное графическое моделирование
MOOC - Probabilistic Graphical Models - Coursera
CS 6190 - Probabilistic Modeling, Spring 2016, University of Utah
10-708 - Probabilistic Graphical Models, Carnegie Mellon University
Probabilistic Graphical Models, Daphne Koller, Stanford University
Probabilistic Models - UNIVERSITY OF HELSINKI
Probabilistic Modelling and Reasoning 2015/16- University of Edinburgh
Probabilistic Graphical Models, Spring 2018 - Notre Dame
Глубокое обучение
Full Stack Deep Learning - Course 2022
Full Stack Deep Learning - Course 2021
NYU Deep Learning Spring 2020
NYU Deep Learning Spring 2021
6.S191: Introduction to Deep Learning - MIT
Intro to Deep Learning and Generative Models Course - Prof Sebastian Raschka
Deep Learning CMU
CS231n Deep Learning for Computer Vision - Winter 2016 Andrej Karpathy - Stanford University
Deep Learning: CS 182 Spring 2021
10-414/714: Deep Learning Systems - CMU (Youtube)
Part 1: Practical Deep Learning for Coders, v3 - fast.ai
Part 2: Deep Learning from the Foundations - fast.ai
Deep learning at Oxford 2015 - Nando de Freitas
Self-Driving Cars — Andreas Geiger, 2021/22 (YouTube)
6.S094: Deep Learning for Self-Driving Cars - MIT
CS294-129 Designing, Visualizing and Understanding Deep Neural Networks (YouTube)
CS230: Deep Learning - Autumn 2018 - Stanford University
STAT-157 Deep Learning 2019 - UC Berkeley
Full Stack DL Bootcamp 2019 - UC Berkeley
Deep Learning, Stanford University
MOOC - Neural Networks for Machine Learning, Geoffrey Hinton 2016 - Coursera
Deep Unsupervised Learning -- Berkeley Spring 2020
Stat 946 Deep Learning - University of Waterloo
Neural networks class - Université de Sherbrooke (YouTube)
CS294-158 Deep Unsupervised Learning SP19
DLCV - Deep Learning for Computer Vision - UPC Barcelona
DLAI - Deep Learning for Artificial Intelligence @ UPC Barcelona
Neural Networks and Applications - IIT Kharagpur
UVA DEEP LEARNING COURSE
Nvidia Machine Learning Class
Deep Learning - Winter 2020-21 - Tübingen Machine Learning
Geometric Deep Learning - AMMI
Math for Deep Learning — Andreas Geiger
Applied Deep Learning 2022 - TU Wien
Neural Networks: Zero to Hero - Andrej Karpathy
CIS 522 - Deep Learning - U Penn
UVA DEEP LEARNING COURSE
Deep Learning (Fall 2020) - Georgia Tech
CS7015 - Deep Learning - Prof. Mitesh M. Khapra - IIT Madras
ETH Zürich | Deep Learning in Scientific Computing 2023
CMU 10 707 Deep Learning fall 2017 by Ruslan Salakhutdinov
UT Austin CS 394D Deep Learning fall 2021, by Philipp KrahenBühl
Stanford CS25 - Transformers United 2023
Обучение с подкреплением
CS234: Reinforcement Learning - Winter 2019 - Stanford University
Introduction to reinforcement learning - UCL
Advanced Deep Learning & Reinforcement Learning - UCL
Reinforcement Learning - IIT Madras
CS885 Reinforcement Learning - Spring 2018 - University of Waterloo
CS 285 - Deep Reinforcement Learning- UC Berkeley
CS 294 112 - Reinforcement Learning
NUS CS 6101 - Deep Reinforcement Learning
ECE 8851: Reinforcement Learning
CS294-112, Deep Reinforcement Learning Sp17 (YouTube)
UCL Course 2015 on Reinforcement Learning by David Silver from DeepMind (YouTube)
Deep RL Bootcamp - Berkeley Aug 2017
Reinforcement Learning - IIT Madras
Reinforcement Learning Course at KTH (FDD3359 - 2022)
Reinforcement Learning Course at ASU, Spring 2022
CS 4789/5789: Introduction to Reinforcement Learning - Cornell
S20/IE613 - Online (Machine) Learning/ Bandit Algorithms
Reinforcement Learning - Fall 2021 chandar-lab
CMU 10 703 Deep Reinforcement Learning & Control fall 2022, by Katerina Fragkiadaki
Продвинутое машинное обучение
Advanced Machine Learning, 2021-2022, Sem I - by Prof. Madhavan Mukund, CMI
18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT
CS 330 - Deep Multi-Task and Meta Learning - Fall 2019 - Stanford University (Youtube)
Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022
ES 661 (2023): Probabilistic Machine Learning - IIT Gandhinagar
Information Retrieval in High Dimensional Data
Обработка естественного языка
CS 224N -Natural Language Processing with Deep Learning - Stanford University (Lectures - Winter 2019) (Lectures - Winter 2021)
CS 224N - Natural Language Processing, Stanford University (Lecture videos)
Stanford XCS224U: Natural Language Understanding I Spring 2023
CS388: Natural Language Processing - UT Austin
CS 124 - From Languages to Information - Stanford University
Neural Networks: Zero to Hero - Andrej Karpathy
fast.ai Code-First Intro to Natural Language Processing (Github)
MOOC - Natural Language Processing - Coursera, University of Michigan
Natural Language Processing at UT Austin (Greg Durrett)
CS224U: Natural Language Understanding - Spring 2019 - Stanford University
Deep Learning for Natural Language Processing, 2017 - Oxford University
Accelerated Natural Language Processing 2015/16- University of Edinburgh
Natural Language Processing - IIT Bombay
CMU Advanced NLP 2021
CMU Neural Nets for NLP 2021
Natural Language Processing - Michael Collins - Columbia University
CMU CS11-737 - Multilingual Natural Language Processing
UMass CS685: Advanced Natural Language Processing (Spring 2022)
Natural Language Processing (CMSC 470)
Компьютерное зрение на основе ML
CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University
CS 198-126: Modern Computer Vision Fall 2022 (UC Berkeley)
Machine Learning for Robotics and Computer Vision, WS 2013/2014 - TU München (YouTube)
Informatics 1 - Cognitive Science 2015/16- University of Edinburgh
Informatics 2A - Processing Formal and Natural Languages 2016-17 - University of Edinburgh
Computational Cognitive Science 2015/16- University of Edinburgh
NOC:Deep Learning For Visual Computing - IIT Kharagpur
Deep Learning for Computer Vision - University of Michigan
Extreme Classification
Анализ временных рядов
02417 Time Series Analysis
Applied Time Series Analysis
Оптимизация
Optimisation for Machine Learning: Theory and Implementation (Hindi) - IIT
EE364a: Convex Optimization I - Stanford University
10-725 Convex Optimization, Spring 2015 - CMU
10-725 Convex Optimization: Fall 2016 - CMU
10-725 Optimization Fall 2012 - CMU
10-801 Advanced Optimization and Randomized Methods - CMU (YouTube)
AM 207 - Stochastic Methods for Data Analysis, Inference and Optimization, Harvard University
Разные темы машинного обучения
Quantum Machine Learning | 2021 Qiskit Global Summer School
CS 6955 - Clustering, Spring 2015, University of Utah
Info 290 - Analyzing Big Data with Twitter, UC Berkeley school of information (YouTube)
CAM 383M - Statistical and Discrete Methods for Scientific Computing, University of Texas
CS224W Machine Learning with Graphs | Spring 2021 | Stanford University
9.520 - Statistical Learning Theory and Applications, Fall 2015 - MIT
Reinforcement Learning - UCL
Regularization Methods for Machine Learning 2016 (YouTube)
Statistical Inference in Big Data - University of Toronto
Reinforcement Learning 2015/16- University of Edinburgh
Reinforcement Learning - IIT Madras
Statistical Rethinking Winter 2015 - Richard McElreath
Music Information Retrieval - University of Victoria, 2014
PURDUE Machine Learning Summer School 2011
Foundations of Machine Learning - Blmmoberg Edu
Introduction to reinforcement learning - UCL
Advanced Deep Learning & Reinforcement Learning - UCL
Web Information Retrieval (Proff. L. Becchetti - A. Vitaletti)
Big Data Systems (WT 2019/20) - Prof. Dr. Tilmann Rabl - HPI
Distributed Data Analytics (WT 2017/18) - Dr. Thorsten Papenbrock - HPI
Introduction to Data-Centric AI - MIT
Parallel Computing and Scientific Machine Learning
Machine Learning System Design - System Design Fight Club
UT Austin ECE 381V Bandits and Online Learning fall 2021, by Sanjay Shakkottai
UCSD MATH 273B Information Geometry and its Applications winter 2022, by Melvin Leok
Cornell ECE 5545 Machine Learning Hardware and Systems spring 2022, by Mohamed Abdelfattah
High Dimensional Analysis: Random Matrices and Machine Learning by Roland Speicher(Youtube)
ACP SUMMER SCHOOL 2023 on Machine Learning for Constraint Programming
EPFL COM 516 Markov Chains and Algorithmic Applications spring 2020, by Olivier Leveque
Компьютерные сети
CS 144 Introduction to Computer Networking - Stanford University, Fall 2013 (Lecture videos)
Computer Networking: A Top-Down Approach
Computer Communication Networks, Rensselaer Polytechnic Institute - Fall 2001 (Videos) (Slides)
Audio/Video Recordings and Podcasts of Professor Raj Jain's Lectures - Washington University in St. Louis (YouTube)
Computer Networks, Tanenbaum, Wetherall Computer Networks 5e - Video Lectures
CSEP 561 - PMP Network Systems, Fall 2013 - University of Washington (Videos)
CSEP 561 – Network Systems, Autumn 2008 - University of Washington (Videos)
Computer Networks - IIT Kharagpur
Introduction to Data Communications 2013, Steven Gordon - Thammasat University, Thailand
Introduction to Complex Networks - RIT
Structural Analysis and Visualization of Networks
Data Communication - IIT Kharagpur
Error Correcting Codes - IISC Bangalore
Information Theory and Coding - IIT Bombay
Complex Network : Theory and Application - IIT Kharagpur
Advanced 3G and 4G Wireless Mobile Communications - IIT Kanpur
Broadband Networks: Concepts and Technology - IIT Bombay
Coding Theory - IIT Madras
Digital Communication - IIT Bombay
Digital Voice & Picture Communication - IIT Kharagpur
Wireless Ad Hoc and Sensor Networks - IIT Kharagpur
Internetworking with TCP/IP by Prof. Dr. Christoph Meinel - HPI
CS798: Mathematical Foundations of Computer Networking - University of Waterloo
Математика для специалиста по информатике
Maths courses all topics covered - Khan Academy
Исчисление
18.01 Single Variable Calculus, Fall 2006 - MIT OCW
18.02 Multivariable Calculus, Fall 2007 - MIT OCW
18.03 Differential Equations, Spring 2010 - MIT OCW
Highlights of Calculus - Gilbert Strang, MIT OCW
Vector Calculus for Engineers - HKUST
Дискретная математика
6.042J - Mathematics for Computer Science, MIT OCW
Computer Science 70, 001 - Spring 2015
CSE 547 Discrete Mathematics, Prof Skiena, University of Stony Brook
Discrete Structures (Summer 2011) - Rutgers, The State University of New Jersey
Discrete Mathematics and Mathematical Reasoning 2015/16 - University of Edinburgh
Discrete Mathematical Structures - IIT Madras
Discrete Structures - Pepperdine University
Вероятность и статистика
Statistics - CrashCourse
6.041 Probabilistic Systems Analysis and Applied Probability - MIT OCW
MIT RES.6-012 Introduction to Probability, Spring 2018 - MIT
Statistics 110 - Probability - Harvard University
STAT 2.1x: Descriptive Statistics | UC Berkeley
STAT 2.2x: Probability | UC Berkeley
MOOC - Statistics: Making Sense of Data, Coursera
MOOC - Statistics One - Coursera
Probability and Random Processes - IIT Kharagpur
MOOC - Statistical Inference - Coursera
131B - Introduction to Probability and Statistics, UCI
STATS 250 - Introduction to Statistics and Data Analysis, UMichigan
Sets, Counting and Probability - Harvard
Opinionated Lessons in Statistics (Youtube)
Statistics - Brandon Foltz
Statistical Rethinking: A Bayesian Course Using R and Stan (Lectures) (Book)
02402 Introduction to Statistics E12 - Technical University of Denmark (F17)
Engineering Probability (ECSE-2500) - RPI
Purdue ECE302 Introduction to Probability for Data Science
Undergraduate Probability with Professor Roman Vershynin
High-Dimensional Probability
Mathematical Statistics
Bayesian Data Analysis
Markov Processes - Spring 2023
Causal Inference Course - Brady Neal
Causal Inference -- Online Lectures (M.Sc/PhD Level)
Machine Learning & Causal Inference: A Short Course
Causal Inference Jonas Peters
Линейная алгебра
Mathematical Foundations of Machine Learning (Fall 2021) - University of Chicago - Rebecca Willett
18.06 - Linear Algebra, Prof. Gilbert Strang, MIT OCW
18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning - MIT OCW
Linear Algebra (Princeton University)
MOOC: Coding the Matrix: Linear Algebra through Computer Science Applications - Coursera
CS 053 - Coding the Matrix - Brown University (Fall 14 videos)
Linear Algebra Review - CMU
A first course in Linear Algebra - N J Wildberger - UNSW
INTRODUCTION TO MATRIX ALGEBRA
Computational Linear Algebra - fast.ai (Github)
ENGR108: Introduction to Applied Linear Algebra—Vectors, Matrices, and Least Squares - Stanford University
MIT 18.S096 Matrix Calculus For Machine Learning And Beyond
10-600 Math Background for ML - CMU
MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
Direct Methods for Sparse Linear Systems - Prof Tim Davis - UFL
36-705 - Intermediate Statistics - Larry Wasserman, CMU (YouTube)
Combinatorics - IISC Bangalore
Advanced Engineering Mathematics - Notre Dame
Statistical Computing for Scientists and Engineers - Notre Dame
Statistical Computing, Fall 2017 - Notre Dame
Mathematics for Machine Learning, Lectures by Ulrike von Luxburg - Tübingen Machine Learning
Essential Mathematics for Machine Learning- July 2018 - IIT Roorkee - YouTube Lectures
Numerics of Machine Learning (Winter 2022/23) - Tübingen Machine Learning
Nonlinear Dynamics and Chaos - Steven Strogatz, Cornell University
Nonlinear Dynamics & Chaos - Virginia Tech
An introduction to Optimization on smooth manifolds (with book) - EPFL
Math Modelling
Large-Scale Convex Optimization: Algorithms & Analyses via Monotone Operators by Ernest Ryu and Wotao Yin
An Overview of Variational Analysis 2021 by Tyrrell Rockafellar
UW AMATH 584 Applied Linear Algebra & Numerical Analysis by Nathan Kutz
UW AMATH 584 Applied Linear Algebra & Introductory Numerical Analysis fall 2005, by Loyce Adams
Stanford CME 206 Introduction to Numerical Methods for Engineering spring 2005, by Charbel Farhat
Stanford CME 200 Linear Algebra with Application to Engineering Computations autumn 2004, by Margot Gerritsen
Stanford CME 302 Numerical Linear Algebra autumn 2007, by Gene Golub
TUe Numerical Linear Algebra 2021, by Martijn Anthonissen
Numerical Linear Algebra fall 2018, by Jaegul Choo
MIT 6.S955 Applied Numerical Algorithms fall 2023, by Justin Solomon
UC Berkeley Math 55 Discrete Mathematics fall 2021, by Nikhil Srivastava
Fundamental Mathematics for Robotics spring 2020, by Ken Tomiyama
Short Course on Casual Inference, by Sanjay Shakkottai
UCLA STAT 100C Linear Models spring 2023, by Arash Amini
MSU Math for Computing
Веб-программирование и интернет-технологии
CS50's Web Programming with Python and JavaScript
Web Design Decal - HTML/CSS/JavaScript Course, University of California, Berkeley
CS 75 Building Dynamic Websites - Harvard University
Internet Technology - IIT Kharagpur
Introduction to Modern Application Development - IIT Madras
CSE 199 - How the Internet Works, Fall 2016 - University of Buffalo
Open Sourced Elective: Database and Rails - Intro to Ruby on Rails, University of Texas (Lectures - Youtube)
CSEP545 - Transaction Processing for E-Commerce, Winter 2012 - University of Washington (Videos)
CT 310 Web Development - Colorado State University
Internet Technologies and Applications 2012, Steven Gordon - Thammasat University, Thailand
CSCI 3110 Advanced Topics in Web Development, Fall 2011 - ETSU iTunes
CSCI 5710 e-Commerce Implementation, Fall 2015 - ETSU iTunes
MOOC - Web Development - Udacity
Web Technologies Prof. Dr. Christoph Meinel - HPI
Теоретические основы CS и языки программирования
MOOC - Compilers - Stanford University
CS 6120: Advanced Compilers: The Self-Guided Online Course - Cornell University
CS 164 Hack your language, UC Berkeley (Lectures - Youtube)
Theory of computation - Shai Simonson
CS 173 Programming Languages, Brown University (Book)
CS Theory Toolkit at CMU 2020
CS 421 - Programming Languages and Compilers, UIUC
CSC 253 - CPython internals: A ten-hour codewalk through the Python interpreter source code, University of Rochester
CSE341 - Programming Languages, Dan Grossman, Spring 2013 - University of Washington
CSEP 501 - Compiler Construction, University of Washington (Lectures - Youtube)
CSEP 505 Programming Languages, Winter 2015 - University of Washington
DMFP - Discrete Mathematics and Functional Programming, Wheaton College
CS 374 - Algorithms & Models of Computation (Fall 2014), UIUC (Lecture videos)
6.045 Automata, Computability, and Complexity, MIT (Lecture Videos)
MOOC - Automata - Jeffrey Ullman - Coursera
CS581 Theory of Computation - Portland State University (Lectures - Youtube)
Theory of Computation - Fall 2011 UC Davis
TDA555 Introduction to Functional Programming - Chalmers University of Technology (Lectures - YouTube)
Ryan O'Donnell Theoretical Computer Science Talks
Philip Wadler Haskell lecture recordings
Functional Programming (2021) - University of Nottingham
Functional Programming - University of Edinburgh - 2016-17
MOOC - Functional Programming Principles in Scala by Martin Odersky
CS294 - Program Synthesis for Everyone
MOOC - Principles of Reactive Programming, Scala - Coursera
Category Theory for Programmers, 2014 - Bartosz Milewski (YouTube)
Теория доказательств, теория типов, теория категорий, верификация
2012 Lectures
2013 Lectures
2014 Lectures
2015 Lectures
2016 Lectures
Latest YT playlists
Inf1 - Computation and Logic 2015 - University of Edinburgh
INFORMATICS 1 - FUNCTIONAL PROGRAMMING - University of Edinburgh (Videos)
Compiler Design - IISC Bangalore
Compiler Design - IIT Kanpur
Principles of Programming Languages - IIT Delhi
Principles of Compiler Design - IISC Bangalore
Functional Programming in Haskell - IIT Madras
Theory of Computation - IIT Kanpur
Theory of Automata, Formal Languages and Computation - IIT Madras
Theory of Computation - IIT Kanpur
Logic for CS - IIT Delhi
Principles of Compiler Design - Swarthmore College
Undergrad Complexity Theory at CMU
Graduate Complexity Theory at CMU
Great Ideas in Theoretical Computer Science at CMU
Another link
Analysis of Boolean Functions at CMU
Theoretical Computer Science (Bridging Course)(Tutorial) - SS 2015
Languages & Translators - UCLouvain LINFO2132
Compiler Design by Sorav Bansal
Встраиваемые системы
EE319K Embedded Systems - UT Austin
EE445L Embedded Systems Design Lab, Fall 2015, UTexas
CS149 Introduction to Embedded Systems - Spring 2011 - UCBerkeley
ECE 4760 Designing with Microcontrollers Fall 2016, Cornell University (Lectures - Youtube)
ECE 5760 - Advanced Microcontroller Design and system-on-chip, Spring 2016 - Cornell University
Internet of Things by Prof. Dr.-Ing. Dietmar P. F. Möller
CSE 351 - The Hardware/Software Interface, Spring 16 - University of Washington (Coursera)
ECE 5030 - Electronic Bioinstrumentation, Spring 2014 - Cornell University
ECE/CS 5780/6780 - Embedded Systems Design, Spring 14 - University of Utah
Embedded Systems Class - Version 1 - 2011 - UNCC
Embedded Systems using the Renesas RX63N Processor - Version 3 - UNCC
Software Engineering for Embedded Systems (WS 2011/12) - HPI University of Potsdam
Embedded Software Testing - IIT Madras
Embedded Systems - IIT Delhi
Embedded Systems Design - IIT Kharagpur
ARM Based Development - IIT Madras
Software Engineering for Self Adaptive Systems - iTunes - HPI University of Potsdam
EE260 Embedded Systems by Robert Paz
IoT Summer School
ECSE 421 - Embedded Systems - McGill
NOC:Advanced IOT Applications - IISc Bangalore
NOC:Design for internet of things - IISc Bangalore
Оценка системы в режиме реального времени
Performance evaluation of Computer systems - IIT Madras
Real Time systems - IIT Karaghpur
EE 380 Colloquium on Computer Systems - Stanford University
System storages - IISc Bangalore
High Performance Computing - IISC Bangalore
2023 High Performance Computing Course Prof Dr - Ing Morris Riedel (2022)
High Performance Computing | Udacity
Компьютерная организация и архитектура
Компьютерная организация
How Computers Work - Aduni
CS 61C - Machine Structures, UC Berkeley (Lectures - InfoCoBuild)
6.004 - Computation Structures Spring 2013, MIT
CS/ECE 3810 Computer Organization, Fall 2015, , University of Utah (YouTube)
Digital Computer Organization - IIT Kharagpur
Computer Organization - IIT Madras
CS-224 - Computer Organization, 2009-2010 Spring, Bilkent University (YouTube playlist)
INFORMATICS 2C - INTRODUCTION TO COMPUTER SYSTEMS (AUTUMN 2016) - University of Edinburgh
Компьютерная архитектура
18-447 - Introduction to Computer Architecture, CMU (Lectures - YouTube - Fall 15)
CS 152 Computer Architecture and Engineering, UC Berkeley
CSEP 548 - Computer Architecture Autumn 2012 - University of Washington
CS/ECE 6810 Computer Architecture, Spring 2016, University of Utah (YouTube)
MOOC - Computer Architecture, David Wentzlaff - Princeton University/Coursera
Computer Architecture - ETH Zürich - Fall 2019
Digital Circuits and Computer Architecture - ETH Zurich - Spring 2017
Computer Architecture - IIT Delhi
Computer Architecture - IIT Kanpur
Computer Architecture - IIT Madras
High Performance Computer Architecture - IIT Kharagpur
BE5B35APO - Computer Architectures, Spring 2022, CTU - FEE (YouTube - Spring 2022) (RISC-V simulator - QtRvSim)
Архитектура параллельного компьютера
15-418 - Parallel Computer Architecture and Programming, CMU (Lecture Videos)
CS 267 Applications of Parallel Computers, Spring 16 - UC Berkeley (YouTube)
MOOC - Heterogeneous Parallel Programming - Coursera
ECE 498AL - Programming Massively Parallel Processors
Parallel Computing - IIT Delhi
Parallel Architectures 2012/13- University of Edinburgh
Проектирование цифровых систем
ELEC2141 Digital Circuit Design, UNSW
Digital Systems Design - IIT Kharagpur
Digital Design Course - 2015 - UNCC
CS1 - Higher Computing - Richard Buckland UNSW
MOOC - From NAND to Tetris - Building a Modern Computer From First Principles (YouTube)
System Validation, TU Delft
High Performance Computing - IISC Bangalore
Introduction to ARM - Open SecurityTraining
Intro x86 (32 bit) - Open SecurityTraining
Intermediate x86 (32 bit) - Open SecurityTraining
Design of Digital Circuits - ETH Zürich - Spring 2019
Onur Mutlu @ TU Wien 2019 - Memory Systems
Memory Systems Course - Technion, Summer 2018
Безопасность
Internet Security (WT 2018/19) - HPI University of Potsdam
6.858 Computer Systems Security - MIT OCW
CS 253 Web Security - Stanford University
CS 161: Computer Security, UC Berkeley
6.875 - Cryptography - Spring 2018- MIT
CSEP590A - Practical Aspects of Modern Cryptography, Winter 2011 - University of Washington (Videos)
CS461/ECE422 - Computer Security - University of Illinois at Urbana-Champaign (Videos)
Introduction to Cryptography, Christof Paar - Ruhr University Bochum, Germany
ECS235B Foundations of Computer and Information Security - UC Davis
CIS 4930/ CIS 5930 - Offensive Computer Security, Florida State University
Introduction to Information Security I - IIT Madras
Information Security - II - IIT Madras
Introduction to Cryptology - IIT Roorkee
Cryptography and Network Security - IIT Kharagpur
18-636 Browser Security, Stanford
Internet Security - Weaknesses and Targets (WT 2015/16) (WT 2012/13 (YouTube))
IT Security, Steven Gordon - Thammasat University, Thailand
Security and Cryptography, Steven Gordon - Thammasat University, Thailand
MOOC - Cryptography - Coursera
MOOC - Intro to Information Security - Udacity
ICS 444 - Computer & Network Security
Privacy and Security in Online Social Networks - IIT Madras
Malware Dynamic Analysis - Open SecurityTraining (YouTube)
CSN09112 - Network Security and Cryptography - Bill Buchanan - Edinburgh Napier
CSN10107 - Security Testing and Network Forensics - Bill Buchanan - Edinburgh Napier
CSN11123 - Advanced Cloud and Network Forensics - Bill Buchanan - Edinburgh Napier
CSN11117 - e-Security - Bill Buchanan - Edinburgh Napier
CSN08704 - Telecommunications - Bill Buchanan - Edinburgh Napier
CSN11128 - Incident Response and Malware Analysis - Bill Buchanan - Edinburgh Napier
Internet Security for Beginners by Dr. Christoph Meinel - HPI
Offensive Security and Reverse Engineering, Chaplain University by Ali Hadi
Компьютерная графика
CS184 - Computer Graphics, Fall 2012 - UC Berkeley
ECS 175 - Computer Graphics, Fall 2009 - UC Davis
6.837 - Computer Graphics - Spring 2017 - MIT
6.838 - Shape Analysis - Spring 2017- MIT
Introduction to Computer Graphics - IIT Delhi
Computer Graphics - IIT Madras
Computer Graphics 2012, Wolfgang Huerst, Utrecht University
CS 5630/6630 - Visualization, Fall 2016, University of Utah (Lectures - Youtube)
Advanced Visualization UC Davis
CSCI E-234 - Introduction to Computer Graphics and GPU Programming, Harvard Extension School
Computer Graphics Fall 2011, Barbara Hecker
Introduction to Graphics Architecture
Ray Tracing for Global Illumination, UCDavis
Rendering / Ray Tracing Course, SS 2015 - TU Wien
ECS 178 Introduction to Geometric Modeling, Fall 2012, UC Davis (iTunes)
Computational Geometry - IIT Delhi
CS 468 - Differential Geometry for Computer Science - Stanford University (Lecture videos)
CMU 15-462/662: Computer Graphics
Обработка изображений и компьютерное зрение
MOOC - Digital Image processing - Duke/Coursera
Digital Image Processing - IIT Kharagpur
Image Processing and Analysis - UC Davis
CS 543 - Computer Vision – Spring 2017 (Recordings)
CAP 5415 - Computer Vision - University of Central Florida(Video Lectures)
EE225B - Digital Image Processing, Spring 2014 - UC Berkeley (Videos - Spring 2006)
EE637 - Digital Image Processing I - Purdue University (Videos - Sp 2011,Videos - Sp 2007)
Computer Vision I: Variational Methods - TU München (YouTube)
Computer Vision II: Multiple View Geometry (IN2228), SS 2016 - TU München (YouTube)
EGGN 510 - Image and Multidimensional Signal Processing - Colorado School of Mines
EENG 512/CSCI 512 - Computer Vision - Colorado School of Mines
Computer Vision for Visual Effects - RPI (YouTube)
Introduction to Image Processing - RPI (YouTube)
CAP 6412 - Advanced Computer Vision - University of Central Florida(Video lectures) (Spring 2018)
Digital Signal Processing - RPI
Advanced Vision 2014 - University of Edinburgh
Photogrammetry Course - 2015/16 - University of Bonn, Germany
MOOC - Introduction to Computer Vision - Udacity
ECSE-4540 - Intro to Digital Image Processing - Spring 2015 - RPI
Machine Learning for Computer Vision - Winter 2017-2018 - UniHeidelberg
High-Level Vision - CBCSL OSU
Advanced Computer Vision - CBCSL OSU
Introduction to Image Processing & Computer Vision - CBCSL OSU
Machine Learning for Computer Vision - TU Munich
Biometrics - IIT Kanpur
Quantitative Big Imaging 2019 ETH Zurich
Multiple View Geometry in Computer Vision
3D Coordinate Systems – Remote Course (GE, 2020) - University of Bonn (2013 lectures)
Modern C++ Course For CV (2020) - University of Bonn
Photogrammetry 1 Course – 2020 - University of Bonn
Photogrammetry II Course 2020/21 - University of Bonn
3D Computer Vision - National University of Singapore
Вычислительная физика
Statistics and Machine Learning for Astronomy
Astronomical data analysis using Python 2021 - NRC IUCAA
SPARC Workshop on Machine Learning in Solar Physics and Space Weather - CESSI IISER Kolkata
Data-Driven Methods and Machine Learning in Atmospheric Sciences - IISC
Computational Astrophysics - AstroTwinCoLo, 2015
Astroinformatics 2019 Conference - Caltech
Space Science with Python - Astroniz
Вычислительная биология
ECS 124 - Foundations of Algorithms for Bioinformatics - Dan Gusfield, UC Davis (YouTube)
CSE549 - Computational Biology - Steven Skiena - 2010 SBU
7.32 Systems Biology, Fall 2014 - MIT OCW
6.802J/ 6.874J Foundations of Computational and Systems Biology - MIT OCW
6.S897 Machine Learning For Healthcare
6.047/6.878 Machine Learning for Genomics Fall 2020 - MIT
6.874 MIT Deep Learning in Life Sciences - Spring 2021 - MIT
6.047/6.878 Public Lectures on Computational Biology: Genomes, Networks, Evolution - MIT
Bio 84 - Your Genes and Your Health, Stanford University
BioMedical Informatics 231 Computational Molecular Biology, Stanford University
BioMedical Informatics 258 Genomics, Bioinformatics & Medicine, Stanford University
03-251: Introduction to Computational Molecular Biology - Carnegie Mellon University
03-712: Biological Modeling and Simulation - Carnegie Mellon University
MOOC - Bioinformatics Algorithms: An Active Learning Approach - UC San Diego/Coursera
Neural Networks and Biological Modeling - Lecturer: Prof. Wulfram Gerstner - EPFL
Video Lectures of Wulfram Gerstner: Computational Neuroscience - EPFL
An Introduction To Systems Biology
Introduction to Bioinformatics, METUOpenCourseWare
MOOC - Algorithms for DNA Sequencing, Coursera
Frontiers of Biomedical Engineering with W. Mark Saltzman - Yale
NOC:Computational Systems Biology - IIT Madras
NOC:BioInformatics:Algorithms and Applications - IIT Madras
Data Science and AI for Neuroscience Summer School - Caltech Neuroscience
Квантовые вычисления
15-859BB: Quantum Computation and Quantum Information 2018 - CMU (Youtube)
Quantum Computation and Information at CMU
Ph/CS 219A Quantum Computation - Prof Preskill - Caltech
Quantum Mechanics and Quantum Computation - Umesh Vazirani
Introduction to quantum computing course 2022 - NYU
Phys 1470 - Foundations of Quantum Computing and Quantum Information - U of Pittsburgh
Introduction to Quantum Computing From a Layperson to a Programmer in 30 Steps (EE225 SJSU)
Quantum Computing Hardware and Architecture (EE274 SJSU)
Quantum Physics for Non-Physicists 2021 - ETH Zurich (2020)
Introduction to Quantum Computing and Quantum Hardware - Qiskit
Understanding Quantum Information and Computation - Qiskit
Lectures in Quantum Computation and Quantum Information (IIT Madras)
Quantum Information and Computing by Prof. D.K. Ghosh
Quantum Computing by Prof. Debabrata Goswami
The Building Blocks of a Quantum Computer: Part 1 - TU Delft
The Building Blocks of a Quantum Computer: Part 2 - TU Delft
Quantum Cryptography - TU Delft
Introduction to Quantum Information
Quantum Computing for Everyone -- Part 1 (Part 2)
Quantum Computer Systems – UChicago
Quantum computing for the determined - Michael Nielsen
Quantum Computing
Робототехника и управление
ROB 101: Computational Linear Algebra - University of Michigan (Youtube - Fall 2021)
ROB 102: Introduction to AI and Programming - University of Michigan
ROB 311: How to Build Robots and Make Them Move - University of Michigan
ROB 320: Robot Operating Systems - University of Michigan
ROB 501: Mathematics for Robotics - University of Michigan (Youtube)
ROB 530 MOBILE ROBOTICS at U of Michigan - WINTER 2022 -- Instructor: Maani Ghaffari
Autorob Winter 2022 - University of Michigan
DeepRob Winter 2023 - University of Michigan
CS 223A - Introduction to Robotics, Stanford University
6.832 Underactuated Robotics - MIT OCW
CS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter Abbeel
CS 287 - Advanced Robotics, Fall 2011, UC Berkeley (Videos)
CMU 16-715 Robot Dynamics 2022 - CMU
CMU 16-745 Optimal Control 2023 - CMU
CS235 - Applied Robot Design for Non-Robot-Designers - Stanford University
Lecture: Visual Navigation for Flying Robots (YouTube)
CS 205A: Mathematical Methods for Robotics, Vision, and Graphics (Fall 2013)
Robotics 1, Prof. De Luca, Università di Roma (YouTube)
Robotics 2, Prof. De Luca, Università di Roma (YouTube)
Robot Mechanics and Control, SNU
Introduction to Robotics Course - UNCC
SLAM Lectures
Introduction to Vision and Robotics 2015/16- University of Edinburgh
ME 597 – Autonomous Mobile Robotics – Fall 2014
ME 780 – Perception For Autonomous Driving – Spring 2017
ME780 – Nonlinear State Estimation for Robotics and Computer Vision – Spring 2017
METR 4202/7202 -- Robotics & Automation - University of Queensland
Robotics - IIT Bombay
Introduction to Machine Vision
6.834J Cognitive Robotics - MIT OCW
Hello (Real) World with ROS – Robot Operating System - TU Delft
Programming for Robotics (ROS) - ETH Zurich
Mechatronic System Design - TU Delft
CS 206 Evolutionary Robotics Course Spring 2020
Foundations of Robotics - UTEC 2018-I
Robotics - Youtube
Robotics and Control: Theory and Practice IIT Roorkee
Mechatronics
ME142 - Mechatronics Spring 2020 - UC Merced
Mobile Sensing and Robotics - Bonn University
MSR2 - Sensors and State Estimation Course (2020) - Bonn University
SLAM Course (2013) - Bonn University
ENGR486 Robot Modeling and Control (2014W)
Robotics by Prof. D K Pratihar - IIT Kharagpur
Introduction to Mobile Robotics - SS 2019 - Universität Freiburg
Robot Mapping - WS 2018/19 - Universität Freiburg
Mechanism and Robot Kinematics - IIT Kharagpur
Self-Driving Cars - Cyrill Stachniss - Winter 2020/21 - University of Bonn)
Mobile Sensing and Robotics 1 – Part Stachniss (Jointly taught with PhoRS) - University of Bonn
Mobile Sensing and Robotics 2 – Stachniss & Klingbeil/Holst - University of Bonn
Aerial Robotics - University of Pennsylvania (UPenn)
Modern Robotics - Northwestern University
MIT 6.4210/6.4212 - Robotic Manipulation - MIT (Youtube)
Industrial Robotics and Automation - IIT (ISM) Dhanbad
MEE5114 Advanced Control for Robotics from Southern University of Science and Technology
Self-Driving Cars — Andreas Geiger
Signal Processing: An Introduction by Nathan Kutz
UC Santa Barbara ME 269 Network Systems, Dynamics and Control fall 2021, by Francesco Bullo
EPFL EE 611 Linear System Theory spring 2020, by Philippe Müllhaupt
EPFL ME 427 Networked Control Systems spring 2020, by Giancarlo Ferrari Trecate
EPFL ME 422 Multivariable Control spring 2020, by Giancarlo Ferrari Trecate
CMU 16 299 Introduction to Feedback Control Systems spring 2022, by Chris Atkeson
MAE 509 Linear Matrix Inequality Methods in Optimal and Robust Control, by Matthew M. Peet
UIUC CS 588 Autonomous Vehicle System Engineering fall 2021, by David Forsyth
Вычислительное финансирование
COMP510 - Computational Finance - Steven Skiena - 2007 HKUST
Computational Finance Course - Prof Grzelak
Financial Engineering Course: Interest Rates and xVA - Prof Grzelak
MOOC - Mathematical Methods for Quantitative Finance, University of Washington/Coursera)
18.S096 Topics in Mathematics with Applications in Finance, MIT OCW
Computational Finance - Universität Leipzig
Machine Learning for Trading | Udacity
ACT 460 / STA 2502 – Stochastic Methods for Actuarial Science - University of Toronto
MMF1928H / STA 2503F – Pricing Theory I / Applied Probability for Mathematical Finance - University of Toronto
STA 4505H – High Frequency & Algorithmic trading - University of Toronto
Mathematical Finance - IIT Guwahati
Quantitative Finance - IIT Kanpur
Financial Derivatives & Risk Management - IIT Roorkee
Financial Mathematics - IIT Roorkee
Разработка блокчейна
Блокчейн и криптовалюты
Blockchain, Solidity, and Full Stack Web3 Development with JavaScript
Blockchain Fundamentals Decal 2018 - Berkeley DeCal
Blockchain for Developers Decal - Spring 2018 - Berkeley DeCal
Cryptocurrency Engineering and Design - Spring 2018 - MIT
15.S12 Blockchain and Money, Fall 2018 - MIT
Blockchain - Foundations and Use Cases
Станьте разработчиком блокчейна
Solidity for Beginners - Dapp University
Master Solidity - Dapp University
IPFS Inter Planetary File System Dapp University
Solidity, Blockchain, and Smart Contract Course – Beginner to Expert Python Tutorial - FreeCodingCamp
Web 3.0 - Build Realtime Decentralized applications
Разное
Проектирование взаимодействия человека и компьютера
CS147 - Introduction to Human-Computer Interaction Design - Stanford
CSEP 510 - Human Computer Interaction
Programming for Designers - COMP1400-T2 (2010) - UNSW
08-763 Intro to HCI for Technology Executives - Fall 2015 - CMU
05-600 HCI Pro Seminar - Fall 2015 - CMU
Разработка игр
CS50's Introduction to Game Development
MIT CMS.611J Creating Video Games, Fall 2014
MOOC - Beginning Game Programming with C# - Coursera
Геопространственность
Introduction to Spatial Data Science, Autumn 2016, University of Chicago
Spatial Regression Analysis, Spring 2017, University of Chicago
Spatial Data Science, Autumn 2017, University of Chicago
Introduction to Geographic Information Systems - IIT Roorkee
SCICOMP - An Introduction to Efficient Scientific Computation, Universität Bremen
CS E-259 XML with Java, Java Servlet, and JSP - Harvard
CSE 40373 - Spr 2009: Multimedia Systems
Exposing Digital Photography - Harvard Extension School
MOOC - Matlab - Coursera
Computing for Computer Scientists - University of Michigan
Linux Implementation/Administration Practicum - Redhat by Tulio Llosa
SIMS 141 - Search Engines - Fall 2005 UCBerkeley
Innovative Computing - Harvard University
Linux Programming & Scripting - IIT Madras
Model Checking - IIT Madras
Virtual Reality - IIT Madras
CS 195 - Social Implications of Computing, Spring 2015 - UC Berkeley (YouTube)
Spatial Databases and Geographic Information Systems - Technische Universität Braunschweig, Germany (in German)
Dependable Systems (SS 2014) - HPI University of Potsdam
Business Process Compliance (WT 2013/14) - HPI University of Potsdam
Design Thinking for Digital Engineering (SS 2018) - Dr. Julia von Thienen - HPI
CS224w – Social Network Analysis – Autumn 2017 - Stanford University
The Missing Semester of Your CS Education
На этом наш пост о CS подошел к концу. Надеюсь вы узнали для себя что-нибудь новое. Если у вас есть то, чем вы можете поделиться сами — пишите в комментариях.
Больше информации о машинном обучении и Data Science в моём аккаунте на Хабре и в телеграм-канале Нейрон, подписывайтесь, чтобы не пропустить будущих статей.
Всем знаний!
