# llSourcell/Learn_Data_Science_in_3_Months

This is the Curriculum for "Learn Data Science in 3 Months" By Siraj Raval on Youtube

Repository: https://github.com/llSourcell/Learn_Data_Science_in_3_Months
Canonical: https://ross.abutalabs.com/products/learn_data_science_in_3_months
License Family: other
Last push: 2020-12-04T04:51:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2864, "days_push": 2098, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2686, forks 951 (observed 2026-08-28T04:07:10.760510+00:00)

## What it is
A curated 12-week curriculum for learning data science, created by Siraj Raval to accompany his YouTube course. It links to free courses, cheat sheets, and weekly Kaggle projects covering Python, statistics, machine learning, deep learning, and databases.

## Use cases
- learn data science from scratch in 3 months
- find a structured self-study curriculum for data science
- get free course links for python statistics and machine learning
- practice data science with kaggle projects
- prepare for a junior data science job
- follow a weekly study plan for machine learning and deep learning

## When to choose
- you want a free, structured, time-boxed roadmap to learn data science
- you prefer learning via linked MOOCs, videos, and hands-on Kaggle projects
- you are a beginner needing guidance on what to study and in what order

## When to avoid
- you need maintained course content rather than a list of external links
- you want an interactive platform or code library instead of a curriculum outline
- you need up-to-date material, as many linked courses may be outdated

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning, deep-learning, data-visualization, etl
- domain: data-science, machine-learning, tutorials, education
- platform: python
- tags: curriculum, self-study, youtube-course, kaggle, 12-week-plan

## Member repositories
- llSourcell/Learn_Data_Science_in_3_Months (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:10.760510+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 2026-08-30T02:17:47.831238+00:00, confidence not recorded.
  - readme: https://github.com/llSourcell/Learn_Data_Science_in_3_Months (fetched 2026-08-28T04:07:10.760510+00:00, sha 401c3b421a0f)
- Data as of 2026-08-30T08:39:29.467469+00:00.