Everything you need to learn about AI

Videos:

1. LLM Introduction: https://www.youtube.com/watch?v=zjkBMFhNj_g

2. LLMs from Scratch: https://www.youtube.com/watch?v=9vM4p9NN0Ts

3. Agentic AI Overview (Stanford): https://www.youtube.com/watch?v=kJLiOGle3Lw

4. Building and Evaluating Agents: https://www.youtube.com/watch?v=d5EltXhbcfA

5. Building Effective Agents: https://www.youtube.com/watch?v=D7_ipDqhtwk

6. Building Agents with MCP: https://www.youtube.com/watch?v=kQmXtrmQ5Zg

7. Building an Agent from Scratch: https://www.youtube.com/watch?v=xzXdLRUyjUg

8. Philo Agents: https://www.youtube.com/playlist?list=PLacQJwuclt_sV-tfZmpT1Ov6jldHl30NR

 

Repos

1. GenAI Agents: https://github.com/nirdiamant/GenAI_Agents

2. Microsoft's AI Agents for Beginners: https://github.com/microsoft/ai-agents-for-beginners

3. Prompt Engineering Guide: https://lnkd.in/gJjGbxQr

4. Hands-On Large Language Models: https://lnkd.in/dxaVF86w

5. AI Agents for Beginners: https://github.com/microsoft/ai-agents-for-beginners

6. GenAI Agents: https://lnkd.in/dEt72MEy

7. Made with ML: https://lnkd.in/d2dMACMj

8. Hands-On AI Engineering:https://github.com/Sumanth077/Hands-On-AI-Engineering

9. Awesome Generative AI Guide: https://lnkd.in/dJ8gxp3a

10. Designing Machine Learning Systems: https://lnkd.in/dEx8sQJK

11. Machine Learning for Beginners from Microsoft: https://lnkd.in/dBj3BAEY

12. LLM Course: https://github.com/mlabonne/llm-course

 

Guides

1. Google's Agent Whitepaper: https://lnkd.in/gFvCfbSN

2. Google's Agent Companion: https://lnkd.in/gfmCrgAH

3. Building Effective Agents by Anthropic: https://lnkd.in/gRWKANS4

4. Claude Code Best Agentic Coding practices: https://lnkd.in/gs99zyCf

5. OpenAI's Practical Guide to Building Agents: https://lnkd.in/guRfXsFK

 

Books:

1. Understanding Deep Learning: https://udlbook.github.io/udlbook/

2. Building an LLM from Scratch: https://lnkd.in/g2YGbnWS

3. The LLM Engineering Handbook: https://lnkd.in/gWUT2EXe

4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://lnkd.in/dJ9wFNMD

5. Building Applications with AI Agents - Michael Albada: https://lnkd.in/dSs8srk5

6. AI Agents with MCP - Kyle Stratis: https://lnkd.in/dR22bEiZ

7. AI Engineering: https://www.oreilly.com/library/view/ai-engineering/9781098166298/

 

Papers

1. ReAct: https://lnkd.in/gRBH3ZRq

2. Generative Agents: https://lnkd.in/gsDCUsWm

3. Toolformer: https://lnkd.in/gyzrege6

4. Chain-of-Thought Prompting: https://lnkd.in/gaK5CXzD

5. Tree of Thoughts: https://lnkd.in/gRJdv_iU

6. Reflexion: https://lnkd.in/gGFMgjUj

7. Retrieval-Augmented Generation Survey: https://lnkd.in/gGUqkkyR

 

Courses:

1. HuggingFace's Agent Course: https://lnkd.in/gmTftTXV

2. MCP with Anthropic: https://lnkd.in/geffcwdq

3. Building Vector Databases with Pinecone: https://lnkd.in/gCS4sd7Y

4. Vector Databases from Embeddings to Apps: https://lnkd.in/gm9HR6_2

5. Agent Memory: https://lnkd.in/gNFpC542

6. Building and Evaluating RAG apps: https://lnkd.in/g2qC9-mh

7. Building Browser Agents: https://lnkd.in/gsMmCifQ

8. LLMOps: https://lnkd.in/g7bHU37w

9. Evaluating AI Agents: https://lnkd.in/gHJtwF5s

10. Computer Use with Anthropic: https://lnkd.in/gMUWg7Fa

11. Multi-Agent Use: https://lnkd.in/gU9DY9kj

12. Improving LLM Accuracy: https://lnkd.in/gsE-4FvY

13. Agent Design Patterns: https://lnkd.in/gzKvx5A4

14. Multi Agent Systems: https://lnkd.in/gUayts9s

 

Newsletters

1. Gradient Ascent: https://lnkd.in/gZbZAeQW

2. DecodingML by Paul: https://lnkd.in/gpZPgk7J

3. Deep (Learning) Focus by Cameron: https://lnkd.in/gTUNcUVE

4. NeoSage by Shivani: https://blog.neosage.io/

5. Jam with AI by Shirin and Shantanu: https://lnkd.in/gQXJzuV8

6. Data Hustle by Sai: https://lnkd.in/gZpdTTYD