generative-ai-for-beginners and Azure-AIGEN-demos

The first project provides an introductory curriculum for generative AI, which could be complemented by the second project's collection of Azure-specific demos, documentation, and accelerators for practical application within that ecosystem.

Azure-AIGEN-demos
56
Established
Maintenance 23/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 13/25
Adoption 10/25
Maturity 8/25
Community 25/25
Stars: 107,907
Forks: 57,877
Downloads:
Commits (30d): 46
Language: Jupyter Notebook
License: MIT
Stars: 749
Forks: 284
Downloads:
Commits (30d): 4
Language: Jupyter Notebook
License:
No Package No Dependents
No License No Package No Dependents

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 Azure-AIGEN-demos

retkowsky/Azure-AIGEN-demos

Azure AI Foundry (demos, documentation, accelerators).

Provides hands-on Jupyter notebooks and reference implementations spanning multiple model families (GPT-5, Mistral, Cohere, FLUX) and enterprise AI patterns including agentic workflows, RAG, real-time interactions, and observability through tracing and custom evaluators. Demonstrates integration with Azure AI Search, Model Router for dynamic request dispatching, and Model Context Protocol (MCP) for agent extensibility. Covers end-to-end scenarios from document AI and image anomaly detection to multi-agent orchestration and safety/compliance evaluation frameworks.

Scores updated daily from GitHub, PyPI, and npm data. How scores work