# microsoft/generative-ai-for-beginners

21 Lessons, Get Started Building with Generative AI

Repository: https://github.com/microsoft/generative-ai-for-beginners
Canonical: https://ross.abutalabs.com/products/generative-ai-for-beginners
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: ai, chatgpt, dall-e, generativeai, gpt, azure, generative-ai, llms, openai, prompt-engineering, language-model, semantic-search, transformers, microsoft-for-beginners
Last push: 2026-08-20T03:43:12+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 83
- inputs: {"age_days": 1171, "days_push": 13, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 118609, forks 62536 (observed 2026-08-28T04:12:24.120056+00:00)

## What it is
A free 21-lesson curriculum from Microsoft teaching how to build applications with generative AI and large language models. It includes Jupyter Notebook lessons covering prompt engineering, RAG, semantic search, and deployment, with multi-language translations.

## Use cases
- learn generative ai from scratch
- beginner course for building llm applications
- learn prompt engineering
- understand how to build rag applications
- tutorial for openai and azure ai apis
- get started with chatgpt and gpt apis
- free curriculum for ai app development

## When to choose
- you are new to generative AI and want a structured, hands-on curriculum
- you prefer learning through Jupyter Notebook code examples
- you want free, MIT-licensed educational material from a reputable source
- you need lessons covering prompt engineering, RAG, and semantic search basics

## When to avoid
- you need production-ready code or a deployable framework rather than tutorials
- you are an advanced practitioner seeking deep, cutting-edge LLM research topics
- you want a non-Python/non-JavaScript learning path

## Facets
- artifact type: learning-resource
- maturity: active
- function: prompt-engineering, rag, llm-inference, developer-tools
- domain: artificial-intelligence, large-language-models, tutorials, education
- platform: python, cross-platform
- tags: generative-ai, course, jupyter-notebooks, openai, azure, beginner-friendly, curriculum

## Member repositories
- microsoft/generative-ai-for-beginners (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:24.120056+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:11:39.003407+00:00, confidence not recorded.
  - readme: https://github.com/microsoft/generative-ai-for-beginners (fetched 2026-08-28T04:12:24.120056+00:00, sha 8858c2ad1c66)
- Data as of 2026-08-30T08:39:29.467469+00:00.