LLM Development Mastery Path

A free, structured, module-wise training program for building applications with Large Language Models — entry level to master level, with runnable Python code in every module and a hands-on project at the end of each level. Focused on applied LLM engineering: prompt engineering, LLM APIs, tool calling, agents, evaluation, and production platforms.

Live site: https://sigilipelli.github.io/llm-dev-mastery-path/

Contents

• Level 1 · Entry — LLM APIs, prompt engineering, structured output, tool calling, a first agent (full lessons)
• Level 2 · Intermediate — advanced prompting, prompt caching, multimodal, MCP, evals, multi-agent systems
• Level 3 · Advanced — transformer internals, tokenizers, local models (Ollama/vLLM), fine-tuning
• Level 4 · Master — training/alignment overview, production LLM platforms, safety & red-teaming, cost at scale

Local development

python3 -m venv .venv
.venv/bin/pip install mkdocs-material
.venv/bin/python -m mkdocs serve

Related

Sibling tracks in the same wave:

• AI/ML Mastery Path
• RAG Mastery Path

The rest of the Mastery Path series:

• Python Mastery Path
• Java Mastery Path
• JavaScript Mastery Path
• TypeScript Mastery Path
• Go Mastery Path
• Rust Mastery Path
• Ruby Mastery Path
• PHP Mastery Path
• C Mastery Path
• C++ Mastery Path
• SQL Mastery Path
• Shell Mastery Path
• R Mastery Path
• Swift Mastery Path
• Kotlin Mastery Path
• Scala Mastery Path
• Dart Mastery Path
• PowerShell Mastery Path
• AWS Mastery Path
• Azure Mastery Path
• GCP Mastery Path
• IBM Cloud Mastery Path
• Adobe Creative Cloud Mastery Path