# qiaoxu123/Self-Driving-Cars

Coursera Open Courses from  University of Toronto

Repository: https://github.com/qiaoxu123/Self-Driving-Cars
Canonical: https://ross.abutalabs.com/products/self-driving-cars
Homepage: https://www.coursera.org/learn/intro-self-driving-cars/home/welcome
Language: Jupyter Notebook
License Family: other
Last push: 2020-04-04T01:59:19+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": 2711, "days_push": 2343, "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 1110, forks 593 (observed 2026-08-28T04:03:37.402037+00:00)

## What it is
A mirror of the University of Toronto's Coursera Self-Driving Cars specialization, containing all course videos, subtitles, PDFs, and an incomplete study notebook. It covers introduction, state estimation and localization, visual perception, and motion planning for autonomous vehicles.

## Use cases
- learn self-driving car engineering for free
- download Coursera self-driving cars course videos and PDFs
- study state estimation and localization for autonomous vehicles
- learn motion planning for self-driving cars
- review visual perception for autonomous driving
- find course notes for the Toronto self-driving cars specialization

## When to choose
- you want offline access to the full Coursera Self-Driving Cars specialization materials
- you are preparing for research or a career in autonomous vehicle engineering
- you prefer reading structured notes alongside course videos

## When to avoid
- you need an actively maintained codebase or software library
- you want official, up-to-date course content with graded assignments
- you need a license-cleared redistribution of course materials

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, data-science
- domain: autonomous-vehicles, tutorials, education, computer-vision, robotics
- platform: python, cross-platform
- tags: self-driving-cars, coursera, course-notes, carla-simulator, jupyter-notebook, state-estimation, motion-planning, visual-perception

## Member repositories
- qiaoxu123/Self-Driving-Cars (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:37.402037+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 2026-08-30T06:43:28.298448+00:00, confidence not recorded.
  - readme: https://github.com/qiaoxu123/Self-Driving-Cars (fetched 2026-08-28T04:03:37.402037+00:00, sha 7dc07b510a80)
  - homepage: https://www.coursera.org/learn/intro-self-driving-cars/home/welcome (fetched 2026-08-29T12:47:14.811341+00:00, sha 0a69c32f62a4)
- Data as of 2026-08-30T08:39:29.467469+00:00.