From Zero to AI-Native Engineer
Build real products with LLMs, agents, and modern AI APIs.
A practitioner-curated track that takes you from understanding transformer basics to shipping production AI features. No PhD required — just curiosity and a code editor.
Curriculum & Syllabus
How LLMs Actually Work
Transformers, tokens, embeddings — plain English.
Your First API Call
Hit the OpenAI API and handle responses correctly.
Prompt Engineering Fundamentals
System prompts, few-shot examples, and output control.
Streaming Responses
Stream tokens to the UI for a ChatGPT-like experience.
Embeddings & Semantic Search
Turn text into vectors and search by meaning.
Build a RAG Pipeline
Ingest a document and answer questions about it.
Function Calling & Tool Use
Connect LLMs to real-world tools and APIs.
Multi-Model Strategy
When to use GPT-4o vs Claude vs Gemini vs local models.
Cost & Token Optimisation
Ship features that don't bankrupt you at scale.
Error Handling & Retries
Make your AI integration production-resilient.
Eval-Driven Development
Test your prompts like you test your code.
Capstone: Ship a Feature
Deploy a real AI-powered feature end-to-end.