Comprehensive, hands-on repository with 22 techniques for prompt engineering, including tutorials and Jupyter notebooks. Topics cover fundamentals to advanced strategies; activity appears to be ongoing with updates through 2026.
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What it is
NirDiamant/Prompt_Engineering is a collection of 22 hands-on tutorials and Jupyter Notebook tutorials focused on prompt engineering techniques, ranging from fundamental concepts to advanced strategies for leveraging large language models.
How it works
The repository provides notebooks and related materials illustrating various prompt engineering techniques, including prompt templates, prompts structures, few-shot learning, chain-of-thought, self-consistency, constrained generation, role prompting, task decomposition, prompt chaining, instruction engineering, and optimization. The README lists a catalog of techniques and links to specific notebooks under each technique.
Getting started
No explicit installation guide is shown in the truncated README excerpt. The repository uses Jupyter Notebook as its primary format, and various techniques reference notebook files such as intro-prompt-engineering-lesson.ipynb and basic-prompt-structures.ipynb. The README also references related projects and a book version; however, there is no explicit installation instruction in the provided section.
Recent releases
RELEASES (latest 0): - none
Traction
stars_7d or stars_1d are not provided in the FACTS block, so this section is omitted as per the guidelines.
Behind the repo
The README mentions sponsorship and community channels (Discord, LinkedIn) but does not provide a linked startup/company page in the provided excerpt. Therefore, this section is omitted.
Caveats
License is listed as none listed. Created in 2024-10-10, last push 2026-07-31. Language is Jupyter Notebook. No explicit license is shown in the provided facts.