AI Prompt Engineering
Prompt engineering is the skill of communicating clearly with AI language models to get accurate, useful outputs. This course teaches the principles behind why prompts succeed or fail, the patterns that work across all major models, and the real-world techniques used in production AI systems.
What you'll learn
Course outline
Free — no account needed
How LLMs Actually Work
A mental model for why AI gives better answers when you communicate more clearly
Anatomy of a Good Prompt
The four components that every effective prompt contains
Chain-of-Thought Prompting
How asking the model to think step-by-step dramatically improves reasoning accuracy
Full course — $49 one-time
Few-Shot Prompting
Examples are the fastest way to communicate exactly what you want
System Prompts and Personas
How to set persistent context and build custom AI assistants for specific tasks
Getting Structured Output
JSON, XML, and schemas — making AI output machine-readable without post-processing headaches
RAG — Giving AI Your Own Knowledge
How retrieval-augmented generation lets you make AI answer questions about your own documents
Prompt Patterns Reference
The 10 patterns that cover 90% of real-world AI use cases — with copy-paste templates
Get the full course
8 lessons — from how LLMs work to production-grade prompting patterns used in real AI systems.