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.
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
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
CSE 142 Computer Programming I (Java Programming), Spring 2016 - University of Washington
CS 106A - Programming Methodology, Stanford University (Lecture Videos)
CS 106B - Programming Abstractions, Stanford University (Lecture Videos)
CmSc 150 - Introduction to Programming with Arcade Games, Simpson College
Introduction to Problem Solving and Programming - IIT Kanpur
Python Boot Camp Fall 2016 - Berkeley Institute for Data Science (BIDS)
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++ (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
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
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)
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
CS 161 - Design and Analysis of Algorithms, Prof. Tim Roughgarden, Stanford University
6.046 - Design and Analysis of Algorithms, Spring 2015 - MIT OCW
CS 473 - Algorithms - University of Illinois at Urbana-Champaign (Notes - Jeff Erickson) (YouTube)
CS 170 Algorithms - UCBerkeley Fall 2018, Youtube Fall 2018,Bilibili 2013 Bilibili
CSEP 521 - Applied Algorithms, Winter 2013 - University of Washington (Videos)
Programming, Data Structures and Algorithms in Python - 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
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
6.889 - Algorithms for Planar Graphs and Beyond (Fall 2011) MIT
6.890 Algorithmic Lower Bounds: Fun with Hardness Proofs - MIT OCW
Introduction to Game Theory and Mechanism Design - IIT Kanpur
CS 270. Combinatorial Algorithms and Data Structures, Spring 2021 (Youtube)
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
CMU 15 859 Algorithms for Big Data fall 2020, by David Woodruff
CS 3650 - Computer Systems - Fall 2020 - Nat Tuck - NEU (Lectures - YouTube)
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)
CSEP 551 Operating Systems Autumn 2014 - University of Washington
CS194 Advanced Operating Systems Structures and Implementation, Spring 2013 InfoCoBuild, UC Berkeley
Distributed Systems
CS 677 - Distributed Operating Systems, Spring 16 - Umass OS
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)
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
EE 380 Colloquium on Computer Systems - Stanford University (Lecture videos)
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
CSEP 544, Database Management Systems, Au 2015 - University of Washington
15-445 - Introduction to Database Systems, CMU (YouTube-2017, YouTube-2018, YouTube-2019, YouTube-2021, YouTube-2022)
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)
Informatics 1 - Data & Analysis 2014/15- University of Edinburgh
Distributed Data Management (WT 2019/20) - Dr. Thorsten Papenbrock - HPI
CS122d - NoSQL Data Management (Spring 21) - Prof. Mike Carey - UC Irvine
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
Informatics 1 - Object-Oriented Programming 2014/15- University of Edinburgh
Software Engineering with Objects and Components 2015/16- University of Edinburgh
Разработка программного обеспечения
Архитектура программного обеспечения
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 508 / CS 508 Manycore Parallel Algorithms spring 2019, by Wen-mei Hwu
Разработка мобильных приложений
MOOC Programming Mobile Applications for Android Handheld Systems - University of Maryland
CS 193p - Developing Applications for iOS, Stanford University
Android App Development for Beginners Playlist - thenewboston
CSSE490 Android Development Rose-Hulman Winter 2010-2011, Dave Fisher
Developing iPad Applications for Visualization and Insight - Carnegie Mellon University
CS50 - Introduction to Artificial Intelligence with Python (and Machine Learning), Harvard OCW
CS 188 - Introduction to Artificial Intelligence, UC Berkeley - Spring 2015
CS221: Artificial Intelligence: Principles and Techniques - Autumn 2019 - Stanford University
CSE 592 Applications of Artificial Intelligence, Winter 2003 - University of Washington
CS322 - Introduction to Artificial Intelligence, Winter 2012-13 - UBC (YouTube)
CS 5804: Introduction to Artificial Intelligence, Spring 2015
Graduate Course in Artificial Intelligence, Autumn 2012 - University of Washington
Informatics 2D - Reasoning and Agents 2014/15- University of Edinburgh
Deductive Databases and Knowledge-Based Systems - Technische Universität Braunschweig, Germany
Artificial Intelligence: Knowledge Representation and Reasoning - IIT Madras
Knowledge Engineering with Semantic Web Technologies by Dr. Harald Sack - HPI
Введение в машинное обучение
Foundations of Machine Learning Boot Camp, Berkeley Simons Institute
CS155 - Machine Learning & Data Mining, 2017 - Caltech (Notes) (2016)
10-601 - Introduction to Machine Learning (MS) - Tom Mitchell - 2015, CMU (YouTube)
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
Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati) (Spring 2022)
CMS 165 Foundations of Machine Learning and Statistical Inference - 2020 - Caltech
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
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
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
Introduction to Machine Learning and Pattern Recognition - CBCSL OSU
Machine Learning Summer School 2013 - Max Planck Institute for Intelligent Systems Tübingen
COM4509/COM6509 Machine Learning and Adaptive Intelligence 2015-16
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
10-418 / 10-618 (Fall 2019) Machine Learning for Structured Data
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
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
Machine Learning Hardware and Systems (Cornell Tech, Spring 2022)
ECE 4760 (Digital Systems Design Using Microcontrollers) at Cornell for the Fall, 2022
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 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
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)
Statistics 202 - Statistical Aspects of Data Mining, Summer 2007 - Google (YouTube)
CS246 - Mining Massive Data Sets, Winter 2016, Stanford University (YouTube)
Data Mining: Learning From Large Datasets - Fall 2017 - 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)
6.0002 Introduction to Computational Thinking and Data Science - MIT OCW
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)
Вероятностное графическое моделирование
Глубокое обучение
Intro to Deep Learning and Generative Models Course - Prof Sebastian Raschka
CS231n Deep Learning for Computer Vision - Winter 2016 Andrej Karpathy - Stanford University
CS294-129 Designing, Visualizing and Understanding Deep Neural Networks (YouTube)
MOOC - Neural Networks for Machine Learning, Geoffrey Hinton 2016 - Coursera
DLAI - Deep Learning for Artificial Intelligence @ UPC Barcelona
CS7015 - Deep Learning - Prof. Mitesh M. Khapra - IIT Madras
UT Austin CS 394D Deep Learning fall 2021, by Philipp KrahenBühl
Обучение с подкреплением
CS234: Reinforcement Learning - Winter 2019 - Stanford University
CS885 Reinforcement Learning - Spring 2018 - University of Waterloo
UCL Course 2015 on Reinforcement Learning by David Silver from DeepMind (YouTube)
CS 4789/5789: Introduction to Reinforcement Learning - Cornell
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
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
CS 124 - From Languages to Information - Stanford University
fast.ai Code-First Intro to Natural Language Processing (Github)
MOOC - Natural Language Processing - Coursera, University of Michigan
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 - Michael Collins - Columbia University
UMass CS685: Advanced Natural Language Processing (Spring 2022)
Компьютерное зрение на основе ML
CS 231n - Convolutional Neural Networks for Visual Recognition, Stanford University
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
Анализ временных рядов
Оптимизация
Разные темы машинного обучения
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
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
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
CS 144 Introduction to Computer Networking - Stanford University, Fall 2013 (Lecture videos)
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)
Introduction to Data Communications 2013, Steven Gordon - Thammasat University, Thailand
Advanced 3G and 4G Wireless Mobile Communications - IIT Kanpur
Internetworking with TCP/IP by Prof. Dr. Christoph Meinel - HPI
CS798: Mathematical Foundations of Computer Networking - University of Waterloo
Исчисление
Дискретная математика
Вероятность и статистика
6.041 Probabilistic Systems Analysis and Applied Probability - MIT OCW
MIT RES.6-012 Introduction to Probability, Spring 2018 - MIT
STATS 250 - Introduction to Statistics and Data Analysis, UMichigan
Statistical Rethinking: A Bayesian Course Using R and Stan (Lectures) (Book)
02402 Introduction to Statistics E12 - Technical University of Denmark (F17)
Линейная алгебра
Mathematical Foundations of Machine Learning (Fall 2021) - University of Chicago - Rebecca Willett
18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning - MIT OCW
MOOC: Coding the Matrix: Linear Algebra through Computer Science Applications - Coursera
CS 053 - Coding the Matrix - Brown University (Fall 14 videos)
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)
Statistical Computing for Scientists and Engineers - 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
An introduction to Optimization on smooth manifolds (with book) - EPFL
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 302 Numerical Linear Algebra autumn 2007, by Gene Golub
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
Web Design Decal - HTML/CSS/JavaScript Course, University of California, Berkeley
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)
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
CS 6120: Advanced Compilers: The Self-Guided Online Course - Cornell University
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)
CS581 Theory of Computation - Portland State University (Lectures - Youtube)
TDA555 Introduction to Functional Programming - Chalmers University of Technology (Lectures - YouTube)
MOOC - Functional Programming Principles in Scala by Martin Odersky
Category Theory for Programmers, 2014 - Bartosz Milewski (YouTube)
Теория доказательств, теория типов, теория категорий, верификация
INFORMATICS 1 - FUNCTIONAL PROGRAMMING - University of Edinburgh (Videos)
Theory of Automata, Formal Languages and Computation - IIT Madras
Theoretical Computer Science (Bridging Course)(Tutorial) - SS 2015
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
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 using the Renesas RX63N Processor - Version 3 - UNCC
Software Engineering for Embedded Systems (WS 2011/12) - HPI University of Potsdam
Software Engineering for Self Adaptive Systems - iTunes - HPI University of Potsdam
Компьютерная организация
CS 61C - Machine Structures, UC Berkeley (Lectures - InfoCoBuild)
CS/ECE 3810 Computer Organization, Fall 2015, , University of Utah (YouTube)
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)
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
Digital Circuits and Computer Architecture - ETH Zurich - Spring 2017
BE5B35APO - Computer Architectures, Spring 2022, CTU - FEE (YouTube - Spring 2022) (RISC-V simulator - QtRvSim)
Архитектура параллельного компьютера
Проектирование цифровых систем
MOOC - From NAND to Tetris - Building a Modern Computer From First Principles (YouTube)
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
Internet Security - Weaknesses and Targets (WT 2015/16) (WT 2012/13 (YouTube))
Security and Cryptography, Steven Gordon - Thammasat University, Thailand
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
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
CS 5630/6630 - Visualization, Fall 2016, University of Utah (Lectures - Youtube)
CSCI E-234 - Introduction to Computer Graphics and GPU Programming, Harvard Extension School
ECS 178 Introduction to Geometric Modeling, Fall 2012, UC Davis (iTunes)
CS 468 - Differential Geometry for Computer Science - Stanford University (Lecture videos)
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
CAP 6412 - Advanced Computer Vision - University of Central Florida(Video lectures) (Spring 2018)
Photogrammetry Course - 2015/16 - University of Bonn, Germany
ECSE-4540 - Intro to Digital Image Processing - Spring 2015 - RPI
Machine Learning for Computer Vision - Winter 2017-2018 - UniHeidelberg
Introduction to Image Processing & Computer Vision - CBCSL OSU
3D Coordinate Systems – Remote Course (GE, 2020) - University of Bonn (2013 lectures)
SPARC Workshop on Machine Learning in Solar Physics and Space Weather - CESSI IISER Kolkata
Data-Driven Methods and Machine Learning in Atmospheric Sciences - IISC
ECS 124 - Foundations of Algorithms for Bioinformatics - Dan Gusfield, UC Davis (YouTube)
6.802J/ 6.874J Foundations of Computational and Systems Biology - MIT OCW
6.874 MIT Deep Learning in Life Sciences - Spring 2021 - MIT
6.047/6.878 Public Lectures on Computational Biology: Genomes, Networks, Evolution - MIT
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
Frontiers of Biomedical Engineering with W. Mark Saltzman - Yale
Data Science and AI for Neuroscience Summer School - Caltech Neuroscience
15-859BB: Quantum Computation and Quantum Information 2018 - CMU (Youtube)
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)
Introduction to Quantum Computing and Quantum Hardware - Qiskit
Lectures in Quantum Computation and Quantum Information (IIT Madras)
The Building Blocks of a Quantum Computer: Part 1 - TU Delft
The Building Blocks of a Quantum Computer: Part 2 - TU Delft
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 501: Mathematics for Robotics - University of Michigan (Youtube)
ROB 530 MOBILE ROBOTICS at U of Michigan - WINTER 2022 -- Instructor: Maani Ghaffari
CS287 Advanced Robotics at UC Berkeley Fall 2019 -- Instructor: Pieter Abbeel
CS235 - Applied Robot Design for Non-Robot-Designers - Stanford University
CS 205A: Mathematical Methods for Robotics, Vision, and Graphics (Fall 2013)
Introduction to Vision and Robotics 2015/16- University of Edinburgh
ME780 – Nonlinear State Estimation for Robotics and Computer Vision – Spring 2017
METR 4202/7202 -- Robotics & Automation - University of Queensland
Hello (Real) World with ROS – Robot Operating System - TU Delft
MSR2 - Sensors and State Estimation Course (2020) - Bonn University
Introduction to Mobile Robotics - SS 2019 - Universität Freiburg
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
MEE5114 Advanced Control for Robotics from Southern University of Science and Technology
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
COMP510 - Computational Finance - Steven Skiena - 2007 HKUST
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
ACT 460 / STA 2502 – Stochastic Methods for Actuarial Science - University of Toronto
STA 4505H – High Frequency & Algorithmic trading - University of Toronto
Блокчейн и криптовалюты
Станьте разработчиком блокчейна
Проектирование взаимодействия человека и компьютера
Разработка игр
Геопространственность
SCICOMP - An Introduction to Efficient Scientific Computation, Universität Bremen
Linux Implementation/Administration Practicum - Redhat by Tulio Llosa
CS 195 - Social Implications of Computing, Spring 2015 - UC Berkeley (YouTube)
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
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!