Practical guides, structured roadmaps, curated tools, and project ideas
Structured learning paths designed to take you from zero to proficient
Learn the fundamentals of Large Language Models in 5 structured days.
Master Retrieval-Augmented Generation from basics to advanced in 3 days.
Understand and build AI agents over 5 focused days of learning.
Comprehensive written guides covering specific topics in detail
Everything you need to know about AI agents — concepts, architecture, and implementation. (~16KB)
Understanding agentic RAG — combining retrieval-augmented generation with agentic workflows. (~15.3KB)
Complete guide to fine-tuning LLMs — methods, tools, and best practices. (~16.1KB)
Deep dive into multimodal large language models — architectures, training, and applications. (~23.2KB)
6-part PDF series explaining commonly used LLM terminology with easy-to-understand definitions.
Comprehensive security guide covering defense-in-depth, guardrails, and AI system protection. (~155KB)
Curated list of AI tools spanning every layer of AI application development.
60 project ideas covering different aspects of AI and generative AI development. (~42KB)
Additional generative AI-specific project suggestions to build your portfolio. (~2.6KB)
Hands-on code resources for building GenAI applications
AWS Bedrock Workshop, LangChain tutorials, Ray LLM apps, Ollama examples, CAMEL-AI cookbook.
LLM Fine-tuning tutorials, PEFT examples by Hugging Face, and free fine-tuning notebooks.
LLM-PlayLab and other comprehensive repositories with multiple transformer-based projects.
Jupyter notebooks on action autonomy, planning autonomy, and agentic AI patterns.