411+ hand picked resources · 30 specialized categories · 100% free · Community driven
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Most "awesome lists" are just link dumps. This one is different:
- Structured for learning — Resources organized by topic AND difficulty (
Beginner→Intermediate→Advanced) - Quality over quantity — Every resource is verified: free, high-quality, and from reputable sources (Stanford, MIT, Google, DeepMind, fast.ai, Hugging Face)
- Practical paths — Not sure where to start? Follow our learning paths below
- Always current — Community maintained and regularly updated
Not sure where to start? Choose your level:
Time: 3-6 months · No prerequisites needed
| Step | What to Learn | Resource |
|---|---|---|
| 1 | Learn Python basics | Python for AI |
| 2 | Build math intuition | Mathematics for AI |
| 3 | Understand ML fundamentals | Machine Learning |
| 4 | Get hands on with frameworks | AI Tools & Frameworks |
| 5 | Try your first project | Data Science |
Time: 2-4 months per specialization
| Interest | Path |
|---|---|
| Build chatbots & AI apps | Generative AI → Prompt Engineering → AI Agents |
| Work with text & language | NLP → Generative AI → AI Research |
| Work with images & video | Computer Vision → AI Art & Image Gen → Multimodal AI |
| Deploy models to production | Deep Learning → MLOps → AI Hardware |
| Healthcare / Finance | Deep Learning → AI in Healthcare or AI in Finance |
| Land an AI job | Machine Learning → Deep Learning → AI Career Prep |
Deep dives into advanced research and systems
| Topic | Resource |
|---|---|
| Multi agent systems | AI Agents |
| Graph based learning | Graph Neural Networks |
| Model interpretability | Explainable AI |
| AI safety & alignment | AI Ethics + AI Security |
| Frontier research | AI Research & Papers |
| Embedded & edge ML | Edge AI & IoT |
Start here if you're new to AI
| Category | What You'll Learn | Resources |
|---|---|---|
| Python for AI | Python programming essentials for ML and data science | 15 |
| Mathematics for AI | Linear algebra, calculus, probability, and optimization | 14 |
| Machine Learning | Core ML algorithms — regression, classification, clustering | 14 |
| Deep Learning | Neural networks, CNNs, RNNs, Transformers | 15 |
| Data Science | Data analysis, visualization, and statistical methods | 14 |
Specialized methodologies for deeper expertise
| Category | What You'll Learn | Resources |
|---|---|---|
| Reinforcement Learning | RL algorithms, policy learning, game AI | 13 |
| Graph Neural Networks | Graph learning, network analysis, geometric DL | 11 |
| Explainable AI (XAI) | Model interpretability, transparency, SHAP, LIME | 12 |
AI applied to specific industries and fields
| Category | What You'll Learn | Resources |
|---|---|---|
| Computer Vision | Image processing, object detection, segmentation | 14 |
| Natural Language Processing | Text analysis, transformers, language models | 14 |
| Audio & Speech Processing | Speech recognition, TTS, audio classification | 13 |
| AI in Healthcare | Medical imaging, drug discovery, clinical AI | 13 |
| AI in Finance | Algorithmic trading, risk modeling, financial ML | 13 |
| Robotics & Autonomous Systems | ROS, robot learning, autonomous vehicles | 14 |
Specialized data processing and architectures
| Category | What You'll Learn | Resources |
|---|---|---|
| Time Series & Forecasting | Predictive models, ARIMA, Prophet, temporal patterns | 13 |
| Recommender Systems | Collaborative filtering, content-based, hybrid methods | 13 |
| Multimodal AI | Vision-language models, cross-modal learning | 13 |
Frameworks, deployment, and hardware
| Category | What You'll Learn | Resources |
|---|---|---|
| AI Tools & Frameworks | PyTorch, TensorFlow, Hugging Face, scikit-learn | 15 |
| MLOps & Deployment | Model serving, pipelines, monitoring, production ML | 14 |
| AI Hardware & Infrastructure | GPUs, TPUs, distributed training, CUDA | 14 |
| Edge AI & IoT | TinyML, on-device ML, embedded systems | 14 |
Responsible, safe, and secure AI development
| Category | What You'll Learn | Resources |
|---|---|---|
| AI Ethics | Bias, fairness, alignment, responsible AI | 14 |
| AI Security & Privacy | Adversarial ML, federated learning, differential privacy | 14 |
The latest in AI capabilities
| Category | What You'll Learn | Resources |
|---|---|---|
| Generative AI | LLMs, text generation, diffusion models | 16 |
| Prompt Engineering | Crafting effective prompts, optimization techniques | 13 |
| AI Agents | Autonomous agents, tool use, multi-agent systems | 14 |
| AI Art & Image Generation | Stable Diffusion, ControlNet, creative AI tools | 14 |
| AI for Code Generation | AI coding assistants, pair programming with AI | 13 |
Career skills and staying current
| Category | What You'll Learn | Resources |
|---|---|---|
| AI Research & Papers | Finding, reading, and understanding AI papers | 14 |
| AI Career & Interview Prep | Interview prep, portfolio building, job market | 14 |
This repository grows because of people like you. Here's how to help:
| Action | How |
|---|---|
| Add a resource | Open a PR adding to the relevant file in /resources/ |
| Fix a broken link | Create an issue or submit a fix directly |
| Suggest a category | Open an issue to discuss |
| Spread the word | Star the repo and share it with others |
See CONTRIBUTING.md for detailed guidelines.
Every resource must be:
- ✅ Free (or free to audit) — no paywalls
- ✅ High quality — from reputable institutions or creators
- ✅ Accessible — working links, no broken pages
- ✅ Educational — teaches something specific and valuable
| Metric | Value |
|---|---|
| Categories | 30 |
| Total Resources | 411+ |
| Resource Types | Courses, Books, Tools, Tutorials, Research |
| Difficulty Levels | Beginner, Intermediate, Advanced |
| License | MIT — use freely |
| Last Updated | February 2026 |
If this helped you learn, please consider:
- Star this repository — helps others discover it
- Fork it — create your own curated version
- Share it — post on Twitter/LinkedIn/Reddit
- Contribute — add resources you've found valuable
Learning AI should be accessible to everyone, everywhere.
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