# krishnaik06/Roadmap-To-Learn-Agentic-AI

Repository: https://github.com/krishnaik06/Roadmap-To-Learn-Agentic-AI
Canonical: https://ross.abutalabs.com/products/roadmap-to-learn-agentic-ai
License: GPL-3.0
License Family: copyleft
Last push: 2025-08-19T06:37:41+00:00

## Health v2 (maintenance only)
Score: 37/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 37, release rhythm 35, longevity 42
- inputs: {"age_days": 588, "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 1015, forks 308 (observed 2026-08-28T04:03:14.045094+00:00)

## What it is
A curated roadmap repository linking YouTube playlists and resources for learning to build agentic AI systems, covering Python, NLP, deep learning, generative AI, and agent frameworks. It is educational material rather than software.

## Use cases
- learn how to build agentic AI systems
- find a step-by-step roadmap for AI agents
- learn generative AI from scratch with projects
- find tutorials on LangChain and agent frameworks
- learn Python, NLP, and deep learning for AI agents
- study multimodal RAG and agentic AI workflows

## When to choose
- you want a structured, video-based learning path for agentic AI
- you are a beginner starting from Python through generative AI
- you prefer curated playlists over scattered searching

## When to avoid
- you need runnable code or a production agent framework
- you want written documentation instead of video tutorials
- you need an up-to-date reference for the latest agent tooling

## Facets
- artifact type: learning-resource
- maturity: active
- function: agent-framework, rag, llm-inference, prompt-engineering
- domain: artificial-intelligence, large-language-models, tutorials, machine-learning
- platform: python
- tags: roadmap, curriculum, youtube-playlists, agentic-ai, generative-ai, learning-path, ai-agents, natural-language-processing

## Member repositories
- krishnaik06/Roadmap-To-Learn-Agentic-AI (main) score 37

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:14.045094+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 2026-08-30T07:11:27.030236+00:00, confidence not recorded.
  - readme: https://github.com/krishnaik06/Roadmap-To-Learn-Agentic-AI (fetched 2026-08-28T04:03:14.045094+00:00, sha ca5addc30f4b)
- Data as of 2026-08-30T08:39:29.467469+00:00.