Prompt_Engineering and prompt_engineering_guide

These are **complements**: the comprehensive tutorial repository provides theoretical foundations and implementation examples that would naturally be referenced or used alongside a workshop guide designed for hands-on learning at a specific conference event.

Prompt_Engineering
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Stars: 64
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Language: Python
License: Apache-2.0
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About Prompt_Engineering

NirDiamant/Prompt_Engineering

This repository offers a comprehensive collection of tutorials and implementations for Prompt Engineering techniques, ranging from fundamental concepts to advanced strategies. It serves as an essential resource for mastering the art of effectively communicating with and leveraging large language models in AI applications.

This project provides tutorials and practical examples for crafting effective instructions to large language models (LLMs). It helps AI developers and practitioners learn how to structure their input so that AI models produce more accurate, relevant, and useful outputs. You'll find guidance on what to include in your prompts and how to refine them for better results.

AI-development natural-language-processing machine-learning-engineering LLM-fine-tuning

About prompt_engineering_guide

DATANOMIQ/prompt_engineering_guide

Prompt Engineering Workshop @ AI Convention 2025 (IHK Schwaben)

This workshop helps professionals learn how to effectively communicate with large language models (LLMs). It takes your problem statements and desired outcomes and guides you through structuring prompts to get the best responses. Anyone who uses AI chatbots or integrates LLMs into their daily work, like marketers, data analysts, or customer support specialists, would benefit.

AI-interaction content-generation data-analysis customer-support knowledge-management

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