A Collection of Learning Resources
Contents
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
- 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
- Friends Transcripts & Scripts — Transcripts and script collection for learning Conversational English
- 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
- GoSeedUp Music — Background focus music for workspace & concentration
- 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
- OpenStax — Free, peer-reviewed open textbooks for Math, Physics & CS
- Understanding AI Models - IBM — Concise visual explanations of AI technology
- Welch Labs — Math, Science, and Machine Learning animations
Learn How to Learn
- 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
- all-agentic-architectures — Collection of AI Agent system design patterns
- Claude Certified Architect – Foundations — Official Anthropic certification for AI architecture
Blogs & Personal Websites
- Andrej Karpathy Blog — Insights on Deep Learning, LLMs, and AI systems
- Brittany Chiang — Software Engineer portfolio & design resources
- Chip Huyen Blog — Machine Learning Systems Design and MLOps
- Colah’s Blog — Visual and intuitive essays on Neural Networks
- Corey Schafer YouTube — High quality Python, Django & Git video tutorials
- Denny’s Blog — Deep Learning research notes by Denny Britz
- Josh W. Comeau — Interactive CSS & Web Development tutorials
- 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
- Dinh Anh Thi Blog — Data Science, Machine Learning & Software Engineering notes by Dinh Anh Thi
- vcubingx — Visual Mathematics and Computer Science concepts
- Yannic Kilcher — AI paper explanations and machine learning news
Coding Platforms
- CodeChef — Practical coding practice and competitive programming
- Exercism — Code practice and mentorship in 70+ programming languages
- 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
- 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
- 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
- awesome-system-design-resources — Free system design interview study guide
- Baymard Ecommerce UX Research — Large-scale UX research & design best practices
- 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
- Snappy UI Optimization with useDeferredValue — Deep dive into React performance optimization by Josh W. Comeau
Deep Learning & Neural Networks
- 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
- 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
- Hướng Dẫn Sử Dụng Local AI Chi Tiết — Detailed guide on running Local LLMs (Ollama, LM Studio) in Vietnamese
- 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
- 100-Days-Of-ML-Code — 100-day study roadmap for machine learning algorithms
- Automate the Boring Stuff with Python — Practical Python programming guide for beginners by Al Sweigart
- 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
- Recommended Python Resources (fast.ai) — Fast.ai curated Python learning guide for Data Science
- Seeing Theory — Visual interactive introduction to probability & statistics
Developer Tools & AI Workflows
- 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.