prompt-engineering-note and chatgpt-prompt-engineering-for-developers

These are complements: one provides structured notes on prompt engineering principles while the other offers a complete course with practical examples, so learners typically use both to deepen understanding from different angles.

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 18/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 17/25
Stars: 263
Forks: 38
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 294
Forks: 33
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
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About prompt-engineering-note

isLinXu/prompt-engineering-note

🔥🔔prompt-engineering-note🔔🔥

Comprehensive learning resource covering LLM fundamentals and prompt engineering best practices through bilingual notes, Jupyter notebooks, and CLI tools for OpenAI API integration. Includes practical examples for summarization, inference, text transformation, and chatbot development, with code runnable directly against OpenAI's API. Supplements the DeepLearning.AI course with curated translations, ChatGPT-generated summaries, executable Python scripts, and a curated project directory for the prompt engineering ecosystem.

About chatgpt-prompt-engineering-for-developers

Kevin-free/chatgpt-prompt-engineering-for-developers

吴恩达《ChatGPT Prompt Engineering for Developers》课程中英版

Contains executable Jupyter notebooks and mind maps demonstrating practical LLM applications using OpenAI's API—including prompt principles, text summarization, sentiment classification, translation, and content generation. Organized with parallel English and Chinese versions to support both international and domestic learners. Includes working code examples that directly implement the course's techniques for building LLM-powered applications.

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