generative-ai-for-beginners and awesome-generative-ai

Maintenance 23/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 6/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 107,907
Forks: 57,877
Downloads:
Commits (30d): 46
Language: Jupyter Notebook
License: MIT
Stars: 3,387
Forks: 661
Downloads:
Commits (30d): 0
Language:
License: CC0-1.0
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About generative-ai-for-beginners

microsoft/generative-ai-for-beginners

21 Lessons, Get Started Building with Generative AI

Covers practical concepts like prompt engineering, RAG architectures, and API integrations across Azure OpenAI, GitHub Models, and OpenAI endpoints, with dual Python/TypeScript code examples for each lesson. The curriculum progresses through foundational AI concepts to production-ready patterns, supported by 50+ automated language translations and optional .NET variant for framework diversity.

About awesome-generative-ai

filipecalegario/awesome-generative-ai

A curated list of Generative AI tools, works, models, and references

Organizes the rapidly evolving GenAI landscape across modalities—text (LLMs, RAG, prompt engineering), image (Stable Diffusion, ControlNet, upscaling), video, audio, and speech—with reverse-chronological ordering to surface recent developments. Covers both applied tools and foundational concepts including embeddings, autonomous agents, LLMOps, and multimodal approaches, alongside ethical critiques and academic papers. Includes practical resources like Google Colab implementations, local inference guides, and community contributions for developers at any expertise level.

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