# krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025

Repository: https://github.com/krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025
Canonical: https://ross.abutalabs.com/products/roadmap-to-learn-generative-ai-in-2025
License: GPL-3.0
License Family: copyleft
Last push: 2025-08-19T06:40:15+00:00

## Health v2 (maintenance only)
Score: 43/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 37, release rhythm 35, longevity 71
- inputs: {"age_days": 996, "days_push": 379, "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 5073, forks 1870 (observed 2026-08-28T04:09:09.384387+00:00)

## What it is
A curated roadmap repository linking YouTube playlists and documentation for learning Generative AI in 2025, covering Python, NLP, deep learning, transformers, and LLMs. It is an educational guide rather than runnable software.

## Use cases
- find a step-by-step path to learn generative AI
- learn Python, NLP, and deep learning prerequisites for LLMs
- discover tutorials on LangChain, GPT-4, Mistral, and Llama
- structure a self-study plan for transformers and RNNs
- get started with generative AI on AWS, Azure, and Google Cloud

## When to choose
- you want a structured, free learning path into generative AI
- you are a beginner needing prerequisites like Python and ML basics
- you prefer video-based tutorials with a clear order

## When to avoid
- you need runnable code or a production tool
- you want an authoritative, peer-reviewed curriculum
- you need content beyond curated external links

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: artificial-intelligence, large-language-models, tutorials
- platform: cross-platform
- tags: roadmap, generative-ai, curriculum, youtube-playlists, llm-learning-path

## Member repositories
- krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025 (main) score 43

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:09.384387+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 2026-08-29T18:02:47.895602+00:00, confidence not recorded.
  - readme: https://github.com/krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025 (fetched 2026-08-28T04:09:09.384387+00:00, sha 3618f68e8d66)
- Data as of 2026-08-30T08:39:29.467469+00:00.