This repo has all the resources you need to become an amazing AI engineer!
Join our free Vibe Coding Bootcamp on Feb 21st and 22nd. We will help you build a SaaS in 48 hours with AI!
If you are new to AI engineering, start by learning the fundamentals of machine learning and then dive into large language models and prompt engineering.
For more applied learning:
- Check out the projects section for hands-on examples!
- Check out the interviews section for advice on how to pass AI engineering interviews!
- Check out the books section for a list of high quality AI engineering books
- Check out the communities section for a list of high quality AI engineering communities to join
- Check out the newsletters section to learn via email
Great list of over 25 books
Top 3 must read books are:
- AI Engineering by Chip Huyen
- Designing Machine Learning Systems
- Build a Large Language Model (From Scratch) by Sebastian Raschka
Great list of communities to join:
Top must-join communities for AI Engineering:
- LLM Providers
- LLM Application Frameworks
- Vector Databases
- Model Training & Fine-Tuning
- Model Serving & Inference
- MLOps & Infrastructure
- Evaluation & Observability
- AI Safety & Guardrails
- Data Labeling & Annotation
- Code Assistants
- Education Companies
- OpenAI Research
- Anthropic Research
- Google AI Blog
- Meta AI Blog
- Microsoft AI Blog
- Hugging Face Blog
- Netflix ML Blog
- Uber AI
- Airbnb AI/ML
- Spotify Engineering (ML)
- LinkedIn AI Blog
- Databricks AI Blog
- Chip Huyen's Blog
- Lilian Weng's Blog
- Sebastian Raschka's Blog
- Eugene Yan's Blog
- Jay Alammar's Blog
- Attention Is All You Need
- BERT: Pre-training of Deep Bidirectional Transformers
- Language Models are Few-Shot Learners (GPT-3)
- Training Language Models to Follow Instructions (InstructGPT)
- LLaMA: Open and Efficient Foundation Language Models
- Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
- Constitutional AI: Harmlessness from AI Feedback
- LoRA: Low-Rank Adaptation of Large Language Models
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
- Scaling Laws for Neural Language Models
- Mixture of Experts
- Direct Preference Optimization (DPO)
- Tree of Thoughts: Deliberate Problem Solving with Large Language Models
- Toolformer: Language Models Can Teach Themselves to Use Tools
- The Prompt Report: A Systematic Survey of Prompting Techniques
Here's a mostly comprehensive list of AI engineering creators:
| Name | YouTube Channel | Follower Count |
|---|---|---|
| 3Blue1Brown | 3Blue1Brown | 6,000,000+ |
| Andrej Karpathy | Andrej Karpathy | 1,000,000+ |
| Yannic Kilcher | Yannic Kilcher | 250,000+ |
| Two Minute Papers | Two Minute Papers | 1,500,000+ |
| Sentdex | Sentdex | 1,300,000+ |
| StatQuest | StatQuest with Josh Starmer | 1,200,000+ |
| DeepLearningAI | DeepLearningAI | 500,000+ |
| AI Explained | AI Explained | 500,000+ |
| Matthew Berman | Matthew Berman | 400,000+ |
| Sam Witteveen | Sam Witteveen | 50,000+ |
| James Briggs | James Briggs | 200,000+ |
| Umar Jamil | Umar Jamil | 200,000+ |
| Dave Ebbelaar | Dave Ebbelaar | 100,000+ |
| AI Jason | AI Jason | 200,000+ |
| Jeremy Howard | Jeremy Howard | 100,000+ |
| Weights & Biases | Weights & Biases | 50,000+ |
| Abhishek Thakur | Abhishek Thakur | 200,000+ |
| Zach Wilson | Data with Zach | 150,000+ |
| Name | LinkedIn Profile | Follower Count |
|---|---|---|
| Andrew Ng | Andrew Ng | 3,000,000+ |
| Chip Huyen | Chip Huyen | 250,000+ |
| Andrej Karpathy | Andrej Karpathy | 500,000+ |
| Sebastian Raschka | Sebastian Raschka | 200,000+ |
| Harrison Chase | Harrison Chase | 100,000+ |
| Jim Fan | Jim Fan | 500,000+ |
| Li Yin | Li Yin | 10,000+ |
| Damien Benveniste | Damien Benveniste | 100,000+ |
| Eugene Yan | Eugene Yan | 50,000+ |
| Hamel Husain | Hamel Husain | 50,000+ |
| Shreya Shankar | Shreya Shankar | 20,000+ |
| Shawn Wang (swyx) | Shawn Wang | 6,000+ |
| Cameron Wolfe | Cameron Wolfe | 50,000+ |
| Zach Wilson | Zach Wilson | 500,000+ |
| Name | X/Twitter Profile | Follower Count |
|---|---|---|
| Andrej Karpathy | @karpathy | 1,000,000+ |
| Jim Fan | @DrJimFan | 500,000+ |
| Swyx | @swyx | 100,000+ |
| Simon Willison | @simonw | 100,000+ |
| Chip Huyen | @chipro | 200,000+ |
| Sebastian Raschka | @rasaborbt1 | 100,000+ |
| Harrison Chase | @hwchase17 | 100,000+ |
| Eugene Yan | @eugeneyan | 50,000+ |
| Hamel Husain | @HasAboreelHusain | 50,000+ |
| Jason Liu | @jxnlco | 30,000+ |
| Lilian Weng | @lilianweng | 100,000+ |
| Zach Wilson | @EcZachly | 30,000+ |
- Latent Space Podcast
- Practical AI
- The TWIML AI Podcast
- Lex Fridman Podcast
- Machine Learning Street Talk
- Gradient Dissent by Weights & Biases
- MLOps.community Podcast
- The Robot Brains Podcast
- No Priors
- Last Week in AI
- Super Data Science: ML & AI Podcast with Jon Krohn
- Eye on AI
- High Agency by Lenny Rachitsky
- Cognitive Revolution
- ThursdAI
Great list of newsletters
Top must follow newsletters for AI engineering:
- The Batch by Andrew Ng
- Ahead of AI by Sebastian Raschka
- Latent Space
- The Sequence
- DataExpert.io Blog
- Sylph.ai Blog
- Google Machine Learning Glossary
- Hugging Face NLP Glossary
- NVIDIA AI Glossary
- Pinecone Learning Center
- OpenAI Documentation
- MLOps Glossary
- Weights & Biases ML Glossary
- RAG (Retrieval-Augmented Generation)
- Prompt Engineering Guide
- LLM Patterns by Eugene Yan
- Building LLM Applications for Production by Chip Huyen
- Agents Design Patterns
- Evaluation-Driven Development
- AdalFlow Design Philosophy
- DeepLearning.AI Short Courses — Free short courses on LLMs, RAG, agents, and more
- fast.ai Practical Deep Learning — Free, top-down practical approach to deep learning
- Stanford CS229: Machine Learning — Andrew Ng's foundational ML course
- Stanford CS224N: NLP with Deep Learning — Chris Manning's NLP course
- Stanford CS25: Transformers United — Seminar on transformers
- Andrej Karpathy's Neural Networks: Zero to Hero — Free YouTube series building neural nets from scratch
- Full Stack Deep Learning — Production ML best practices
- Hugging Face NLP Course — Free comprehensive NLP/transformers course
- MLOps Zoomcamp by DataTalksClub — Free MLOps course
- Made With ML — ML + MLOps course focused on production
- LLM University by Cohere — Free LLM fundamentals course
- Maxime Labonne's LLM Course — Comprehensive LLM roadmap on GitHub
- Prompt Engineering for Developers by DeepLearning.AI
- AWS Certified Machine Learning - Specialty
- Google Cloud Professional Machine Learning Engineer
- Microsoft Azure AI Engineer Associate (AI-102)
- NVIDIA Deep Learning Institute Certifications
- TensorFlow Developer Certificate
- Databricks Machine Learning Associate
- DeepLearning.AI TensorFlow Developer Professional Certificate
- Stanford Online AI Professional Program