# nickmccullum/algorithmic-trading-python

The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python

Repository: https://github.com/nickmccullum/algorithmic-trading-python
Canonical: https://ross.abutalabs.com/products/algorithmic-trading-python
Language: Jupyter Notebook
License Family: other
Last push: 2024-06-20T07:31:16+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2225, "days_push": 804, "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 2877, forks 2558 (observed 2026-08-28T04:07:27.477862+00:00)

## What it is
A Jupyter Notebook repository accompanying freeCodeCamp's free YouTube course on algorithmic trading in Python. It contains course materials for building equal-weight index funds and quantitative momentum and value investing strategies using API-based stock data.

## Use cases
- learn algorithmic trading in python
- build a quantitative momentum investing strategy
- create an equal-weight S&P 500 index fund
- learn quantitative value investing
- follow a free algorithmic trading course
- practice pulling stock data via APIs in python

## When to choose
- you want a free, beginner-friendly introduction to algorithmic trading concepts
- you learn best by following video courses with hands-on notebooks
- you want to practice building simple quant strategies in Python

## When to avoid
- you need production-ready trading or backtesting software
- you want live trading with a broker integration
- you need a maintained library with a license and active support

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: trading, data-science, developer-tools
- domain: fintech, education, data-science, tutorials
- platform: python, cross-platform
- tags: algorithmic-trading, jupyter-notebooks, free-course, quantitative-finance, momentum-strategy, value-investing

## Member repositories
- nickmccullum/algorithmic-trading-python (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:27.477862+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 2026-08-30T07:35:41.615835+00:00, confidence not recorded.
  - readme: https://github.com/nickmccullum/algorithmic-trading-python (fetched 2026-08-28T04:07:27.477862+00:00, sha 05ec636f47cd)
- Data as of 2026-08-30T08:39:29.467469+00:00.