# NeuromatchAcademy/course-content

NMA Computational Neuroscience course

Repository: https://github.com/NeuromatchAcademy/course-content
Canonical: https://ross.abutalabs.com/products/course-content
Homepage: https://compneuro.neuromatch.io
Language: Jupyter Notebook
License: CC-BY-4.0
License Family: other
Topics: neuroscience, machine-learning, dynamic-systems, stochastic-processes
Last push: 2026-07-14T14:48:31+00:00

## Health v2 (maintenance only)
Score: 94/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 92, release rhythm 93, longevity 100
- inputs: {"age_days": 2306, "days_push": 50, "days_rel": 50, "gap_med": 2, "n_releases_24m": 26}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3118, forks 1092 (observed 2026-08-28T04:07:44.224088+00:00)

## What it is
The Neuromatch Academy Computational Neuroscience course content: a free, openly licensed curriculum of Jupyter notebook tutorials, videos, and schedules. It teaches computational neuroscience topics alongside machine learning, dynamic systems, and stochastic processes.

## Use cases
- learn computational neuroscience from scratch
- find jupyter notebook tutorials on dynamic systems
- self-study a neuroscience and machine learning curriculum
- teach a computational neuroscience summer course
- access free course materials on stochastic processes in neural systems

## When to choose
- you want a structured, free curriculum in computational neuroscience
- you prefer hands-on Jupyter notebook tutorials
- you need openly licensed teaching material you can adapt

## When to avoid
- you need production software or a library
- you want a formal degree or accredited certification
- you lack the stated math and programming prerequisites

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, data-science, developer-tools
- domain: machine-learning, education, tutorials
- platform: python, cross-platform
- tags: computational-neuroscience, jupyter-notebooks, course-material, open-curriculum, dynamic-systems, stochastic-processes, neuroscience

## Member repositories
- NeuromatchAcademy/course-content (main) score 94

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:44.224088+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 2026-08-30T07:26:38.397649+00:00, confidence not recorded.
  - readme: https://github.com/NeuromatchAcademy/course-content (fetched 2026-08-28T04:07:44.224088+00:00, sha 4e2fbe64e029)
  - homepage: https://compneuro.neuromatch.io (fetched 2026-08-29T09:41:40.629759+00:00, sha 44136fa355b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.