# krishnaik06/Perfect-Roadmap-To-Learn-Data-Science-In-2025

Repository: https://github.com/krishnaik06/Perfect-Roadmap-To-Learn-Data-Science-In-2025
Canonical: https://ross.abutalabs.com/products/perfect-roadmap-to-learn-data-science-in-2025
License: GPL-3.0
License Family: copyleft
Last push: 2025-08-19T06:23:43+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": 1004, "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 4109, forks 1534 (observed 2026-08-28T04:08:35.707906+00:00)

## What it is
A curated roadmap repository linking YouTube playlists and resources for learning data science in 2025, covering Python, statistics, EDA, and feature engineering. It is a learning guide rather than software, organized as a step-by-step curriculum with video links.

## Use cases
- learn data science from scratch
- find a data science roadmap for 2025
- curated youtube playlists for python and statistics
- plan a study path for machine learning
- resources for EDA and feature engineering

## When to choose
- you want a structured, video-based learning path for data science
- you prefer free curated playlists over paid courses

## When to avoid
- you need runnable code or a software library
- you want text-based documentation rather than video tutorials

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: data-science, machine-learning, tutorials
- platform: cross-platform
- tags: roadmap, curated-links, youtube-playlists, data-science-learning-path, 2025

## Member repositories
- krishnaik06/Perfect-Roadmap-To-Learn-Data-Science-In-2025 (main) score 43

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:35.707906+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 2026-08-29T18:23:12.696815+00:00, confidence not recorded.
  - readme: https://github.com/krishnaik06/Perfect-Roadmap-To-Learn-Data-Science-In-2025 (fetched 2026-08-28T04:08:35.707906+00:00, sha 6dc4cd9b7315)
- Data as of 2026-08-30T08:39:29.467469+00:00.