AI Learning Resources

Building Agentic AI Systems

Andrew Ng — agents, tool calling, memory

Finetuning Large Language Models

When to fine-tune vs prompt, instruction tuning, and LoRA — by Sharon Zhou

Prompt Engineering Guide

Zero-shot, few-shot, chain-of-thought, ReAct and advanced techniques — DAIR.AI

ChatGPT Prompt Engineering for Developers

Best practices for prompting, building with the OpenAI API

Building Applications with Vector Databases

Semantic search, RAG, and anomaly detection with Pinecone — hands-on

Hugging Face NLP Course

Transformers, fine-tuning, and the full HuggingFace ecosystem

Generative AI with Large Language Models

LLM lifecycle, fine-tuning, RLHF — by DeepLearning.AI and AWS

Fine-tune a Pretrained Model

Hands-on fine-tuning with HuggingFace Trainer API, datasets, and evaluation

LLMOps

Production LLM pipelines with Google Cloud — versioning, testing, and deployment at scale

RAG in Practice

A foundational framework to adapt RAG systems as new tools and methods emerge

Evaluating and Debugging Generative AI

Trace, evaluate, and iterate on LLM outputs using Weights & Biases

Introduction to Generative AI

Broad overview of GenAI concepts and use cases

Princeton: Understanding Large Language Models

Deep academic course on LLM internals, scaling laws, and alignment

LangChain for Production

Workflows and orchestration with LangChain

Applied AI

Multi AI Agent Systems with crewAI

LLMOps: Building Real-World Applications With Large Language Models

From curated awesome-list

Advanced Retrieval for AI with Chroma

From curated awesome-list

Training & Fine-Tuning LLMs for Production

From curated awesome-list

Prompt Engineering with Llama 2

From curated awesome-list

TradingAgents: Multi-Agents LLM Financial Trading Framework

Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context b

🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

🗂 The essential checklist for modern web development, for humans and AI agents

Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code

An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message ga