Quick links
A compact, at-a-glance index of all resources in this site.
| Name | Domain | Type | Difficulty | Time |
|---|---|---|---|---|
| 3Blue1Brown Neural Networks Video Series | Foundations | tutorial | Beginner | 5 hours |
| A Gentle Introduction to Graph Neural Networks | Foundations | tutorial | Beginner To Intermediate | 2–4 hours |
| Agents4Science: Agentic Scientific Discovery Platforms | Foundations | online course | Advanced | ≈10–15 hours (lecture slides + assignments) |
| An Introduction to Statistical Learning | Foundations | online textbook | Intermediate | 30–60 hours (full book with labs) |
| Bayesian Modeling and Computation in Python | Foundations | online textbook | Intermediate | 20–40 hours |
| BoTorch | Foundations | software | Intermediate | - |
| Deep Neural Networks Video Course | Foundations | online course | Beginner | 8–10 hours (video playlist) |
| Dive into Deep Learning | Foundations | online textbook | Beginner | 30–60 hours |
| Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges | Foundations | online textbook | Advanced | 20–40 hours |
| Homemade Machine Learning | Foundations | tutorial | Beginner To Intermediate | 15–30 hours (working through demos and notebooks) |
| Hugging Face | Foundations | dataset | Beginner | - |
| Interpretable Machine Learning | Foundations | online textbook | Intermediate | 20–30 hours |
| Introduction to Scientific ML | Foundations | online textbook | Intermediate | TODO |
| LLM Visualization | Foundations | tutorial | Intermediate | 1–2 hours |
| Machine Learning for Beginners (Microsoft) | Foundations | online course | Beginner | 40–60 hours (12-week, 26-lesson curriculum) |
| Machine Learning for Everyone (In Simple Words) | Foundations | tutorial | Beginner | 1–2 hours |
| Machine Learning Introduction (Coursera) | Foundations | online course | Beginner | 2 months part-time (~10 hours/week) |
| Machine Learning Refined – Course Materials | Foundations | online course | Beginner To Intermediate | 40–60 hours (online notes, exercises, and slides) |
| Mathematics for Machine Learning Specialization | Foundations | online course | Intermediate | 4 weeks part-time (~10 hours/week) |
| Practical Deep Learning for Coders (fast.ai) | Foundations | online course | Intermediate | 30+ hours (video lessons plus notebooks) |
| Python for Physicists | Foundations | course | Beginner | 12 hours |
| PyTorch | Foundations | software | Beginner | - |
| scikit-learn | Foundations | software | Beginner | - |
| Software Carpentry Lessons | Foundations | tutorial | Beginner | 10–20 hours (Unix shell, Git, and Python/R lessons) |
| TensorFlow | Foundations | software | Intermediate | TODO |
| The Python Tutorial (Official Documentation) | Foundations | tutorial | Beginner | 10–20 hours (full read-through with exercises) |
| Understanding Deep Learning | Foundations | online textbook | Intermediate | 15–30 hours |
| BayBE | Chemistry | software | Beginner | - |
| Data Analytics in Chemistry (CHEM70012 — Imperial College) | Chemistry | online course | Beginner To Intermediate | ≈8–12 hours (workshop notebooks + data-analysis modules) |
| Data-Driven Chemistry (University of Edinburgh) | Chemistry | online course | Beginner | 12–20 hours (10 workshop units) |
| Deep Learning for Molecules and Materials | Chemistry | online textbook | Beginner To Intermediate | 15–30 hours |
| DScribe | Chemistry | software | Beginner | - |
| EPFL AI for Chemistry course | Chemistry | online course | Intermediate | 10–20 hours |
| GAUCHE | Chemistry | software | Intermediate | - |
| Intro to Machine Learning in Chemistry (ML4chemArg) | Chemistry | online course | Beginner To Intermediate | 10–15 hours (notebook-based course) |
| Introduction to Python for Chemists (Imperial College) | Chemistry | tutorial | Beginner | ≈5–10 hours (notebooks + exercises) |
| Is Life Worth Living? — Cheminformatics Blog by @iwatobipen | Chemistry | tutorial | Beginner To Intermediate | Varies (many short posts, individual topics) |
| ML4Chem | Chemistry | software | Intermediate | 2–4 hours (tutorials) |
| MORDRED | Chemistry | software | Beginner | - |
| RDKit | Chemistry | software | - | - |
| Reinforcement Learning for ChemEng | Chemistry | tutorial | Intermediate To Advanced | 5–10 hours (notebook tutorials) |
| Scientific Computing for Chemists with Python | Chemistry | online textbook | Beginner To Intermediate | 10 - 15 hours (basics) + 15-30 hours (advanced topics) |
| STK | Chemistry | software | Beginner | - |
| STKO | Chemistry | software | Beginner | - |
| Automated Experiment (UTK Spring 2023) | Materials | online course | Intermediate | 8–12 hours (lecture slides + notebooks) |
| Digital Materials Foundry – Experimental Materials Data Library (Henry Royce Institute) | Materials | dataset | - | - |
| Machine Learning for Materials (MATE70026 — Imperial College) | Materials | online course | Intermediate | ≈12–16 hours (lectures + notebook modules + assignments) |
| Machine Learning for Materials: From PCA to ChatGPT (UTK MSE Fall 2023) | Materials | online course | Intermediate To Advanced | 30–40 hours (selected modules, readings, and notebooks) |
| MatBench – Benchmark Datasets for Materials Property Prediction | Materials | dataset | - | - |
| MatChem Dataset Repository | Materials | dataset | Beginner | - |
| Materials Informatics (MSE5540/6640, University of Utah) | Materials | online course | Intermediate | 30–50 hours (lectures, homeworks, and worked examples) |
| Materials Informatics Video Tutorials (Taylor Sparks) | Materials | tutorials | Beginner | - |
| Materials Project | Materials | dataset | - | - |
| Porous Material AI Gym: Open Datasets for Machine Learning on Porous Materials | Materials | dataset | - | - |