# upb-lea/reinforcement_learning_course_materials

Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University

Repository: https://github.com/upb-lea/reinforcement_learning_course_materials
Canonical: https://ross.abutalabs.com/products/reinforcement_learning_course_materials
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: reinforcement-learning, control, teaching, teaching-materials, python, latex, prediction, machine-learning, course, course-materials, online-videos, online-learning, tutorial, lecture, lecture-notes, open-educational-resources, open-education-resources, open-education, jupyter, jupyter-notebooks
Last push: 2026-01-05T12:00:53+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 60, release rhythm 52, longevity 100
- inputs: {"age_days": 2235, "days_push": 240, "days_rel": 240, "gap_med": 89.5, "n_releases_24m": 3}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1191, forks 258 (observed 2026-08-28T04:03:56.242833+00:00)

## What it is
Open course materials for a university reinforcement learning course, including LaTeX lecture slides, tutorial exercises with solutions, Jupyter notebooks, and recorded lecture videos. Licensed CC BY 4.0 for reuse by students and lecturers.

## Use cases
- learn reinforcement learning from scratch
- find lecture notes on Markov decision processes and temporal-difference learning
- set up a university RL course with existing slides and exercises
- practice RL with tutorial tasks and solutions
- self-study reinforcement learning with videos
- get Jupyter notebook exercises for RL algorithms

## When to choose
- you want a complete, structured RL curriculum with videos and exercises
- you are a lecturer reusing open course material under CC BY
- you prefer theory-first learning with worked solutions

## When to avoid
- you need a production RL library or framework
- you want only code without lectures or theory
- you need a license permitting redistribution beyond CC BY terms

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, reinforcement-learning, developer-tools
- domain: reinforcement-learning, education, machine-learning, tutorials
- platform: python, cross-platform
- tags: lecture-notes, open-educational-resources, jupyter-notebooks, latex-slides, online-videos, university-course, self-learning

## Member repositories
- upb-lea/reinforcement_learning_course_materials (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:56.242833+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 2026-08-30T06:22:59.151963+00:00, confidence not recorded.
  - readme: https://github.com/upb-lea/reinforcement_learning_course_materials (fetched 2026-08-28T04:03:56.242833+00:00, sha 67c681a5395c)
- Data as of 2026-08-30T08:39:29.467469+00:00.