AI & ML Course Hub
Dec 7, 2025
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3 min read
🚀 My AI & ML Learning Journey
Whether you’re a beginner or an advanced learner, I hope this inspires and supports your own AI/ML adventure!
📚 Table of Contents
- Mathematics for ML
- Machine Learning Theory
- Deep Learning
- Language Models & NLP
- Generative AI & LLMs
- Scientific ML / Physics-based ML
- Reinforcement Learning
- Computer Vision
- Robotics & AI Systems
- Software Engineering & Tools
- How to Use
- Contributing
- Acknowledgments
🔢 Mathematics for ML
Foundational mathematics courses to build a strong base for machine learning.
| Course | Description | Link |
|---|---|---|
| Boosting Python (PDE MOOC) | Learn iterative methods for numerical Partial Differential Equations (PDEs) with Python. | Link |
| EPFL Mathematics of Data | Explore the mathematical theories underpinning data analysis and computation. | Link |
| MIT Matrix Calculus | Dive into matrix calculus techniques from MIT’s IAP 2023 course. | Link |
| Numerical Algorithms | Study numerical methods and algorithms from KAIST. | Link |
🧠 Machine Learning Theory
Deepen your understanding of the theoretical foundations of machine learning.
| Course | Description | Link |
|---|---|---|
| ML Theory Class | A theoretical ML course by Stephen Becker, covering core concepts. | Link |
| Bayesian ML and Info Processing | Technical course on Bayesian methods for ML and information processing. | Link |
| Advanced Topics in ML | Explore Reproducing Kernel Hilbert Spaces (RKHS) and Gaussian Processes. | Link |
| Reproducing Kernel Hilbert Space | Study RKHS in the context of analytic function spaces. | Link |
🔥 Deep Learning
Comprehensive resources for mastering deep learning techniques.
| Course | Description | Link |
|---|---|---|
| Deep Learning by Alfredo Canziani | A thorough NYU course covering deep learning fundamentals. | Link |
| Fundamentals of ML | An introductory lecture series on deep learning concepts. | Link |
| DeepCourse | Open deep learning course by Arthur Douillard. | Link |
| CS1470 - Deep Learning | Brown University’s comprehensive deep learning curriculum. | Link |
| Applied Deep Learning | Practical deep learning applications by Maziar Raissi. | Link |
🗣 Language Models & NLP
Courses focused on natural language processing and language models.
| Course | Description | Link |
|---|---|---|
| Stanford CS336 | Build language models from scratch with Stanford’s course. | Link |
| CMU Advanced NLP S2025 | Advanced topics in NLP from Carnegie Mellon University. | Link |
✨ Generative AI & LLMs
Resources for understanding generative AI and large language models.
| Course | Description | Link |
|---|---|---|
| Learning in Undirected Models | CS228 notes on undirected graphical models. | Link |
| GenAI Handbook | In-depth guide to structured state-space models. | Link |
| LLM Course | Colab-based roadmap for learning large language models. | Link |
⚛️ Scientific ML / Physics-based ML
Courses blending machine learning with scientific and physical modeling.
| Course | Description | Link |
|---|---|---|
| PDE & Finite Difference | Foundations of scientific ML with PDEs and finite differences. | Link |
| Solving PDEs MOOC | Learn numerical methods for solving PDEs. | Link |
| Physics-Informed ML | Combine ML with physical modeling techniques. | Link |
| Diffusion Models, ETH | Study sampling and stochastic models at ETH Zurich. | Link |
| SciML Book | MIT’s textbook on scientific machine learning. | Link |
🎮 Reinforcement Learning
Resources for learning reinforcement learning algorithms and theory.
| Course | Description | Link |
|---|---|---|
| Spinning Up in RL | OpenAI’s guide to reinforcement learning algorithms. | Link |
| Math Foundations of RL | Theoretical grounding in RL with a mathematical focus. | Link |
👁 Computer Vision
Courses on computer vision techniques and applications.
| Course | Description | Link |
|---|---|---|
| Tübingen Computer Vision | Comprehensive computer vision course from the University of Tübingen. | Link |
🤖 Robotics & AI Systems
Explore the intersection of AI and robotics.
| Course | Description | Link |
|---|---|---|
| AI4ALL - Robotics | Introduction to robotics and AI for educational purposes. | Link |
🛠 Software Engineering & Tools
Tools and practices for research and software development in AI.
| Course | Description | Link |
|---|---|---|
| Research Software Engineering with Python | Turing Institute’s course on software engineering for research. | Link |
| RSE GitHub Repo | Companion materials for the RSE course. | Link |
📌 Acknowledgments
- A huge thanks to the universities, researchers, and open course creators who make these resources freely available.
