233 resources. 110 concepts. 100 experts. One free AI learning system.

• 23 learning topics

• 110 AI concepts 100 expert profiles

• 90+ curated videos

• 90+ courses and sites

• 70+ GitHub repos

• 60+ books and papers

• 30+ data fields per expert

• 10 concept categories

• 6 learning phases

• 4 practice milestones, 18 weeks start to finish

I built a complete AI learning system and published it as a website. Free. No login. No email capture. No upsell. Note, happy to hear your recommendation

• Roadmap: https://venkatapagadala.com/notebook/ai/roadmap

• Concepts Encyclopedia : https://venkatapagadala.com/notebook/ai/encyclopedia

• Top 100 Contributors: https://venkatapagadala.com/notebook/ai

Here's what's inside.

The Roadmap - 23 topics, 90+ videos, 90+ courses, 70+ repos

Roadmap: https://venkatapagadala.com/notebook/ai/roadmap

• 6 phases. 18 weeks. Zero to building LLM applications.

• 🟢 Foundations → 🔵 Python & Math → 🟡 Machine Learning → 🟠 Deep Learning → 🔴 NLP & LLMs → 🟣 Specialize & Build

• Every topic: 3-4 videos, 3-4 courses, 3-4 GitHub repos, 2-3 books, recommended tools.

• Videos from 3Blue1Brown, Andrej Karpathy, Andrew Ng, StatQuest, freeCodeCamp, Stanford CS229, CS231n, CS224n, MIT 6.S191.

• Courses from fast.ai, Coursera, Kaggle, Hugging Face, Khan Academy, Google, DeepLearning.AI.

• Repos: nanoGPT (38K stars)

• scikit-learn (60K), huggingface/transformers (140K), LangChain (100K), d2l-en (55K), stable-diffusion-webui (140K).

• 4 practice milestones built into the sequence. Not suggestions - checkpoints. Build an ML project. Build a deep learning project. Build an LLM application. Build a portfolio.

• Topics most roadmaps skip: prompt engineering, AI safety and ethics, data engineering, model evaluation, AI agents, and reading research papers.

The Encyclopedia - 110 concepts, 10 categories, 3 difficulty levels

Every concept from "What is Data?" to State Space Models.

🧠 Concepts Encyclopedia : https://venkatapagadala.com/notebook/ai/encyclopedia

Each entry: description in plain English, key terms, prerequisites, real-world applications, best free resource link.

• 🏗️ Foundations - 15 concepts

• 📊 Machine Learning - 20 concepts

• 🧠 Deep Learning - 20 concepts

• 💬 NLP & Language Models - 17 concepts

• 👁️ Computer Vision - 8 concepts

• 🎮 Reinforcement Learning - 8 concepts

• 🎨 Generative AI - 8 concepts

• ⚙️ MLOps & Infrastructure - 7 concepts

• 🛡️ AI Safety & Ethics - 4 concepts

• 🔬 Advanced Research - 3 concepts

Prerequisite chains connect every concept. You always know what comes next.

The People - 100 experts, 30+ fields each, every link clickable

Geoffrey Hinton. Yoshua Bengio. Yann LeCun. Andrej Karpathy. Andrew Ng. Demis Hassabis. Ilya Sutskever. Fei-Fei Li. Ian Goodfellow. Sam Altman. Dario Amodei. And 89 others.

📚 Top 100 Contributors: https://venkatapagadala.com/notebook/ai

Every profile:

• Bio.

• Affiliation.

• Country.

• Specialty.

• AI segment.

• Expert type. Website. Twitter/X. GitHub. LinkedIn. YouTube. Google Scholar. Substack.

• Education. PhD advisor. Awards and recognition.

• Citations. Company valuation.

• Books. Notable talks.

• Podcasts with clickable links.

• Interviews with clickable links.

• Top projects. Top papers. GitHub followers.

• GitHub pinned repos. Board memberships.

• Key influence.

15 AI segments: Foundation Models & LLMs, Computer Vision, Robotics, AI Safety, NLP, Generative AI, Reinforcement Learning, ML Theory, Open Source AI, AI Hardware, AI for Science, AI Education, Enterprise AI, AI Ethics, AI Agents.

5 expert types: Researcher, Industry Leader, Founder/CEO, Educator, Policy Advocate.Global coverage: USA, Canada, UK, China, France, Germany, Israel, Switzerland, India, South Korea, and more.