A Collection of Learning Resources
The resources listed in this note have not been verified yet. They are included so that they can be checked at a later time. The order is random.
“You do not rise to the level of your goals. You fall to the level of your systems.” – James Clear
Icon Legend:
- GitHub Repository
- Book or Document
- Learned or Noted
- Video or YouTube
- Favorite Resource
- Course or MOOC
General Resources
| Resource | Type | Description |
|---|---|---|
| 3Blue1Brown | Visual math and neural network animations | |
| 500+ AI Projects with Code | Machine Learning, Deep Learning, CV & NLP projects | |
| Adam Lucek | Developer portfolio, GitHub and YouTube channel | |
| Andrej Karpathy | Deep Learning and Neural Networks lectures | |
| AWS Machine Learning Blog | Official AWS blog for ML architecture & tutorials | |
| Build Your Own X | Recreate programming technologies from scratch | |
| DeepLearning.AI | Start or advance your career in AI | |
| Deep Learning Drizzle | Curated list of high-quality Deep Learning courses | |
| NVIDIA Deep Learning Institute | Hands-on AI and GPU training and certification | |
| DeepTutor | Multi-agent document interactive learning system | |
| Developer Roadmaps - roadmap.sh | Community-created developer learning roadmaps | |
| Distill | Clear and visual machine learning research articles | |
| From 0 to Research Scientist Guide | Self-study guide for AI research scientists | |
| Google AI | Google AI tools, research, training and skills | |
| Google Cloud Skills Boost | Google Cloud training, labs and certifications | |
| Google Skills | Free training and certifications for Google Cloud | |
| Hugging Face Learn | Open-source Machine Learning and NLP courses | |
| Hướng Dẫn Tự Học Trí Tuệ Nhân Tạo | AI self-study guides in Vietnamese | |
| Collection of Kaggle Solutions | Winning Kaggle solutions and competitive ideas | |
| Kaggle Learn Tutorials | Micro-courses for Python, Data Viz, and Pandas | |
| Microsoft Learn Training | Microsoft official developer and cloud courses | |
| Understanding AI Models - IBM | Concise visual explanations of AI technology | |
| Welch Labs | Math, Science, and Machine Learning animations |
Learn How to Learn
| Resource | Type | Description |
|---|---|---|
| A Mind for Numbers | How to excel at math and science by Dr. Barbara Oakley | |
| How To Learn Any Skill So Fast It Feels Illegal | Actionable techniques for rapid skill acquisition | |
| How to Read a Book | Classic guide to intelligent reading by Mortimer Adler | |
| Learning How To Learn Book | Guide for kids and teens on effective learning | |
| Learning How to Learn Coursera | Popular MOOC on mental tools and memory techniques | |
| Make It Stick | Science of successful learning through retrieval practice | |
| Pragmatic Thinking and Learning | Refactor your wetware and cognitive habits by Andy Hunt | |
| Reading Research Papers by Andrew Ng | Efficient workflow for digesting technical papers | |
| Understanding How We Learn | Visual guide to cognitive psychology in learning |
Agentic AI
| Resource | Type | Description |
|---|---|---|
| all-agentic-architectures | Collection of AI Agent system design patterns | |
| Claude Certified Architect – Foundations | Official Anthropic certification for AI architecture |
Blogs & Personal Websites
| Resource | Type | Description |
|---|---|---|
| Andrej Karpathy Blog | Insights on Deep Learning, LLMs, and AI systems | |
| Denny’s Blog | Deep Learning research notes by Denny Britz | |
| Colah’s Blog | Visual and intuitive essays on Neural Networks | |
| Chip Huyen Blog | Machine Learning Systems Design and MLOps | |
| Lil’Log | In-depth technical AI posts by Lilian Weng | |
| Raúl Gómez Blog | Computer Vision and Deep Learning research | |
| ruder.io | NLP and Machine Learning research updates | |
| serrano.academy | Friendly Machine Learning video tutorials | |
| sentdex | Python programming and Machine Learning tutorials | |
| StatQuest with Josh Starmer | Statistics and Machine Learning broken down step by step | |
| vcubingx | Visual Mathematics and Computer Science concepts | |
| Yannic Kilcher | AI paper explanations and machine learning news |
Coding Platforms
| Resource | Type | Description |
|---|---|---|
| CodeChef | Practical coding practice and competitive programming | |
| HackerRank | Technical interview prep and skill assessments | |
| Kaggle Solutions | Repository of competitive machine learning code | |
| LeetCode | Standard platform for Data Structures & Algorithms practice |
Computer Science
| Resource | Type | Description |
|---|---|---|
| CS Video Courses | Comprehensive list of Computer Science video courses | |
| coding-interview-university | Complete CS study plan for software engineering jobs | |
| CS50x 2025 - Harvard | Introduction to Computer Science by David J. Malan | |
| roadmap.sh | Visual learning paths for CS, DevOps, and Frontend | |
| Learn to Program: Crafting Quality Code | Software quality course by University of Toronto | |
| Teach Yourself Computer Science | Curated guide for self-taught software engineers | |
| The Art of Debugging | Comprehensive open book on software debugging | |
| Visualize the Brrr | Learn GPU hardware architecture interactively |
Data Structures & Algorithms
| Resource | Type | Description |
|---|---|---|
| Abdul Bari Channel | Clear and comprehensive lectures on Algorithms | |
| Algorithms by Jeff Erickson | Free open textbook on Algorithm design | |
| Algorithms Part I | Princeton course by Sedgewick & Wayne | |
| Algorithms Part II | Advanced algorithms course from Princeton | |
| awesome-algorithms | Curated list of algorithm learning resources | |
| UCSD DSA Specialization | 6-course specialization in Data Structures | |
| PrincetonAlgorithms | Code repository for Algorithms 4th edition | |
| Stanford Algorithms Specialization | Stanford algorithm course taught by Tim Roughgarden |
Design Patterns & System Design
| Resource | Type | Description |
|---|---|---|
| awesome-system-design-resources | Free system design interview study guide | |
| Designing Data-Intensive Applications | Industry-standard book on distributed systems by Kleppmann | |
| Design Patterns (Gang of Four) | Classic reference book on object-oriented design patterns | |
| Head First Design Patterns | Beginner-friendly visual guide to OOP patterns | |
| Introduction to ML Systems - Harvard | Course on building production machine learning systems | |
| python-patterns | Collection of design patterns implemented in Python | |
| Refactoring.guru | Visual interactive guide to refactoring and design patterns |
Deep Learning & Neural Networks
| Resource | Type | Description |
|---|---|---|
| Awesome Deep Learning | Curated list of deep learning tutorials and papers | |
| Deep Learning Specialization | Landmark 5-course series by Andrew Ng | |
| DeepMind x UCL Lecture Series | Advanced lectures on AI and Reinforcement Learning | |
| Dive into Deep Learning | Interactive book with code in PyTorch, JAX and NumPy | |
| Deep Learning Book | Definitive textbook by Goodfellow, Bengio & Courville | |
| NYU Deep Learning Course | Course taught by Turing Award winner Yann LeCun | |
| fast.ai Practical Deep Learning | Hands-on deep learning for coders | |
| Neural Networks Series | Visual introduction to backpropagation by 3Blue1Brown | |
| Neural Networks: Zero To Hero | Build micrograd and GPT from scratch with Andrej Karpathy | |
| Understanding Deep Learning | Comprehensive textbook by Simon J.D. Prince |
Generative AI & Large Language Models
| Resource | Type | Description |
|---|---|---|
| AI Engineering: Foundation Models | Building production applications with LLMs by Chip Huyen | |
| Awesome LLM Apps | LLM apps built with AI Agents and RAG architectures | |
| Build LLM Applications from Scratch | Step-by-step guide to training and building LLMs | |
| ChatGPT Prompt Engineering | Short course by DeepLearning.AI and OpenAI | |
| Generative AI for Beginners - Microsoft | 18-lesson curriculum on GenAI by Microsoft | |
| Hands-On Large Language Models | Code repository for language understanding models | |
| LLM Visualization | Interactive 3D visualization of how GPT architecture works | |
| LLMs-from-scratch | Build a Transformer LLM from scratch in PyTorch | |
| Stanford CS229: LLMs Lecture | Building Large Language Models lecture series | |
| Prompt Engineering Guide - Lil’Log | Comprehensive technical reference on prompt techniques |
Machine Learning & Mathematics
| Resource | Type | Description |
|---|---|---|
| 100-Days-Of-ML-Code | 100-day study roadmap for machine learning algorithms | |
| Hands-On Machine Learning (3rd Ed) | Practical guide using Scikit-Learn, Keras & TensorFlow | |
| Machine Learning Cơ Bản | Machine Learning fundamentals explained in Vietnamese | |
| ML Specialization by Andrew Ng | Updated Stanford ML course series in Python | |
| Pattern Recognition and Machine Learning | Classic foundational textbook by Christopher Bishop | |
| Seeing Theory | Visual interactive introduction to probability & statistics |
Developer Tools & AI Workflows
| Resource | Type | Description |
|---|---|---|
| Connected Papers | Visual graph tool to explore academic research papers | |
| Cursor AI Code Editor | Next-generation AI-first code editor | |
| Claude Code by Anthropic | Agentic CLI tool for codebase interaction | |
| Lightning.ai | Platform for building and training multi-GPU AI models | |
| Vercel AI SDK | Library for building AI streaming web applications | |
| spec-kit | Toolkit for Spec-Driven Software Development |
This collection is maintained and updated periodically. Feel free to explore the links above to deepen your technical knowledge.