Prompt Engineering Techniques
A repository of 22 hands-on Jupyter Notebook tutorials on prompt engineering, from basic templates through chain-of-thought, self-consistency and tree-of-thought prompting.
This repository is a collection of prompt engineering tutorials and implementations, ranging from basic concepts to advanced strategies for using large language models, with 22 hands-on tutorials covering everything from basic prompt templates to chain-of-thought, self-consistency and tree-of-thought prompting.
A companion, paid course, "Prompt to Production," teaches the methods and paradigms behind building reliable, efficient, modular production systems with AI across 17 modules, each pairing a video lecture with a hands-on lab. The repository separately offers a tool that writes a documentation layer for another repository from its own code and scores what a coding agent knew about that repository before and after, tested against six well-known open-source Python projects.