Ross ROSS = Recommend OSS · open-source software intelligence for agents

cs109/content resource

Official content for Harvard CS109 observed · 2026-08-28

github.com/cs109/content · homepage · Jupyter Notebook · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 4759
  • days_rel: n/a
  • days_push: 1352
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1793 stars · 1565 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official course content for Harvard's CS109 Data Science course, including homework assignments, lecture supplements, and labs as Jupyter notebooks. It covers data wrangling, visualization, machine learning, Bayesian statistics, and web scraping, and is freely available for self-study.

Use cases

  • learn data science from scratch
  • self-study harvard cs109 course
  • practice data science homework with solutions
  • learn pandas and matplotlib with jupyter notebooks
  • learn bayesian statistics and cross-validation
  • find data science course assignments and labs

When to choose

  • you want a free, structured university-level data science curriculum
  • you learn best from hands-on Jupyter notebook assignments with solutions
  • you want coverage of classic data science topics like EDA, regression, and Bayesian methods

When to avoid

  • you need up-to-date course material - the content dates from 2013-2015
  • you want deep learning or modern LLM topics, which are in CS109B instead
  • you need a maintained library or tool rather than educational content

Facets

learning-resource · maturity maintenance

data-science machine-learning data-visualization web-scraping nlp data-science education tutorials machine-learning python cross-platform jupyter-notebooks harvard course-material assignments labs statistics pandas scikit-learn bayesian

2 sources

Member repositories

RepositoryRoleHealth v2
cs109/contentmain32

For agents

markdown · JSON · MCP: product_card(name="cs109/content")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem