LLM Development Mastery Path¶

Mastery Path

BOOTCAMP

VINOD BHANUJA

A structured, module-wise training program that takes you from your first LLM API call to master-level LLM application engineering — prompt engineering, tool calling, agents, evaluation, and production platforms — with runnable Python code in every module and a hands-on project at the end of each level.

This track is about building applications with LLMs, not training models from scratch. Examples use the Anthropic API (Claude), and every concept — messages, system prompts, tool calling, streaming — maps 1:1 to other providers such as OpenAI and Google.

How the program is organized¶

Level	Focus	Modules
Level 1 · Entry	LLM APIs, prompt engineering, structured output, tool calling, a first agent	9 topics + 1 project
Level 2 · Intermediate	Advanced prompting, caching, multimodal, MCP, evals, multi-agent systems	9 topics + 1 project
Level 3 · Advanced	Transformer internals, tokenizers, local models, vLLM, fine-tuning	9 topics + 1 project
Level 4 · Master	Training/alignment overview, production platforms, safety, cost at scale	9 topics + 1 capstone

How to use this site¶

Work through each level in order — later modules assume earlier ones.
Every topic page has runnable Python code — you'll need Python 3.10+ and an Anthropic API key (each lesson says exactly where the key is needed).
Each level ends with a project that combines everything learned in that level.
Use the search bar (top of the page) to jump straight to a topic.

Start here → Level 1 · Entry

Sibling tracks¶

AI/ML Mastery Path — classical machine learning foundations
RAG Mastery Path — retrieval-augmented generation pipelines (this site links there instead of duplicating RAG content)

🎥 Prefer video? Watch the Mastery Path video series on YouTube — Shorts and full walkthroughs of these lessons.