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Generative AI Curricula · Awesome GitHub Repositories

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Awesome GitHub RepositoriesGenerative AI Curricula

Explore 2 awesome GitHub repositories matching education & learning resources · Generative AI Curricula. Refine with filters or upvote what's useful.

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  3. Curricula and Instructional Design
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  6. Generative AI Curricula

Awesome Generative AI Curricula GitHub Repositories

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  • microsoft/generative-ai-for-beginners

    microsoft/generative-ai-for-beginners

    106,618GitHubView on GitHub↗

    This project is a comprehensive, open-source educational curriculum designed to guide developers through the mastery of generative artificial intelligence. It provides a structured learning path that covers foundational concepts, prompt engineering, and the practical application of large language models. The repository

    Walks through the complete lifecycle of building, deploying, and maintaining generative applications.

    Jupyter Notebookaiazurechatgpt
  • mlabonne/llm-course

    mlabonne/llm-course

    75,340GitHubView on GitHub↗

    This project is a comprehensive educational curriculum and engineering handbook focused on the lifecycle of large language models. It serves as a structured knowledge base for machine learning practitioners, covering the fundamental mathematical and architectural principles of transformer-based sequence modeling, as we

    Supplies educational notebooks and guides explaining implementation techniques for fine-tuning machine learning models.

    courselarge-language-modelsllm

Explore sub-tags

  • Conversational AI TutorialsInstructional guides for building interactive chat interfaces using large language models.
  • Generative AI Development GuidesComprehensive learning modules covering the end-to-end lifecycle of building, deploying, and maintaining generative AI applications.
  • Generative AI TutorialsInstructional content focused on building applications with specific generative AI models.
Image Generation Modules
Instructional content focused on the development and integration of generative models for visual media.
  • Low-Code AI DevelopmentInstructional modules for building AI applications using minimal manual coding techniques.
  • Model Fine-Tuning GuidesEducational resources and guides explaining the benefits, use cases, and implementation techniques for fine-tuning machine learning models.
  • Retrieval Augmented Generation ModulesInstructional content covering the integration of external data sources with language models via vector-based retrieval.