Zero to Hero With 250 FREE Online Programming and Computer Science Courses from Top Universities Part 3.24 min read
I’ve been sharing with you 5 parts(1.1, 1.2, 2.1, 2.2, 3.1) of this series about free online programming and computer science courses. ‘216 courses’ from the last few parts that contains a lot of practical things. But it’s not the end! Now I am happy to share with you last 44 courses as well as the last part of these series articles. I hope you enjoy it!
250 FREE ONLINE PROGRAMMING & COMPUTER SCIENCE COURSES FROM TOP UNIVERSITIES PART 3.2
Six years ago, universities like MIT and Stanford first opened up free online courses to the public. Today, more than 800 schools around the world have created thousands of free online courses.
You can also go to Class Central’s homepage to find many free courses available up to 10000 from top universities.
I’ve sorted these courses into the following categories based on their difficulty level as well as 3 parts of this topic:
- Beginner
- Intermediate
- Advanced
The first sections will be for beginners(part 1.1, part 1.2), the second will be for those who are looking for intermediate courses(part 2.1, part 2.2) and the rest will be for advanced courses(part 3.1, part 3.2). All of these are aggregated in 250 free courses.
In this part I will introduce you to the courses that are suitable for advanced learners, if you are looking for beginner courses click here, intermediate courses click here.
ADVANCED PROGRAMMING COURSES PART 3.2 (44)
- MATLAB et Octave pour débutants from École Polytechnique Fédérale de Lausanne
- Nature, in Code: Biology in JavaScript from École Polytechnique Fédérale de Lausanne
- Менеджмент информационной безопасности from Higher School of Economics
- Методы и средства защиты информации from Higher School of Economics
- Обработка изображений from Higher School of Economics
- Introduction to Formal Concept Analysis from Higher School of Economics
- Practical Reinforcement Learning from Higher School of Economics
- Addressing Large Hadron Collider Challenges by Machine Learning from Higher School of Economics
- Matrix Factorization and Advanced Techniques from University of Minnesota
- 機器學習基石下 (Machine Learning Foundations) — -Algorithmic Foundations from National Taiwan University
- 人工智慧：搜尋方法與邏輯推論 (Artificial Intelligence — Search & Logic)from National Taiwan University
- System Validation: Automata and behavioural equivalences from EIT Digital
- System Validation (3): Requirements by modal formulas from EIT Digital
- Embedded Hardware and Operating Systems from EIT Digital
- System Validation (4): Modelling Software, Protocols, and other behaviour from EIT Digital
- Learn TensorFlow and deep learning, without a Ph.D. from Google
- Machine Learning Crash Course with TensorFlow APIs from Google
- Infrastructure as Code from Microsoft
- Deep Learning Explained from Microsoft
- Introduction to Artificial Intelligence (AI) from Microsoft
- DevOps Testing from Microsoft
- DevOps for Databases from Microsoft
- DevOps Practices and Principles from Microsoft
- Advanced C++ from Microsoft
- Sparse Representations in Image Processing: From Theory to Practice from Technion — Israel Institute of Technology
- Sparse Representations in Signal and Image Processing: Fundamentalsfrom Technion — Israel Institute of Technology
- Cyber-Physical Systems: Modeling and Simulation from University of California, Santa Cruz
- Statistical Machine Learning from Carnegie Mellon University
- Introduction to OpenStack from Linux Foundation
- Blockchain for Business — An Introduction to Hyperledger Technologiesfrom Linux Foundation
- Introduction to Cloud Foundry and Cloud Native Software Architecturefrom Linux Foundation
- Approximation Algorithms Part II from École normale supérieure
- Mathematics for Machine Learning: Linear Algebra from Imperial College London
- Mathematics for Machine Learning: Multivariate Calculus from Imperial College London
- Reliable Distributed Algorithms, Part 2 from KTH Royal Institute of Technology
- Mathematics for Machine Learning: PCA from Imperial College London
- Computer System Design: Advanced Concepts of Modern Microprocessorsfrom Chalmers University of Technology
- Deep Learning for Natural Language Processing from University of Oxford
- Cutting Edge Deep Learning For Coders, Part 2 from fast.ai
- Cloud Computing Security from University System of Maryland
- Continuous Integration and Deployment
- Deep Learning Summer School
- Access Controls from (ISC)²
- Networks and Communications Security from (ISC)²
YOU CAN REFER TO PART 3.1 HERE.
