A source-based collection of 22 hands-on Jupyter Notebook tutorials for learning prompt engineering from basic structures through advanced strategies. It is intended for educational demonstrations rather than a documented managed service.
Project overview
A source-based collection of 22 hands-on Jupyter Notebook tutorials for learning prompt engineering from basic structures through advanced strategies. It is intended for educational demonstrations rather than a documented managed service.
Project type
AI Coding
Use cases
Learning & Education
Deployment
Refer to project documentation
License
License pending
Best for
People seeking structured, notebook-based practice with prompt engineering techniques, from basic concepts to advanced strategies.
Covers basic prompt structures, templates, and variables.
Demonstrates zero-shot, few-shot, and chain-of-thought prompting in notebooks.
Includes implementations of self-consistency, constrained generation, and role prompting.
Limitations and risks
A custom non-commercial license restricts commercial use.
GPU needs, hardware requirements, operating-system support, model requirements, cost dependency, data boundary, telemetry, and interaction mode are not documented.
Getting started
Clone the repository with git, navigate to the all_prompt_engineering_techniques directory, then open and follow a notebook's implementation guide.
Evidence and sources
GitHub project description: 22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
README: Our goal is to provide a valuable resource for everyone - from beginners taking their first steps in AI to seasoned practitioners pushing the boundaries of what's possible.
README: Prompt engineering is at the forefront of artificial intelligence, revolutionizing the way we interact with and leverage AI technologies.
README: 22 hands-on tutorials covering everything from basic prompt templates to advanced techniques like chain-of-thought, self-consistency, and tree-of-thought prompting.
README: Learn prompt engineering techniques from beginner to advanced levels