# yandexdataschool/Practical_RL

A course in reinforcement learning in the wild

Repository: https://github.com/yandexdataschool/Practical_RL
Canonical: https://ross.abutalabs.com/products/practical_rl
Language: Jupyter Notebook
License: Unlicense
License Family: permissive
Topics: reinforcement-learning, course-materials, deep-learning, deep-reinforcement-learning, git-course, mooc, tensorflow, pytorch, pytorch-tutorials, keras, hacktoberfest
Last push: 2026-03-31T20:00:24+00:00

## Health v2 (maintenance only)
Score: 57/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 75, release rhythm 8, longevity 100
- inputs: {"age_days": 3509, "days_push": 155, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6564, forks 1806 (observed 2026-08-28T04:09:45.257481+00:00)

## What it is
An open-source reinforcement learning course taught at HSE and YSDA, designed to be friendly to online students in English and Russian. It provides lectures, seminars, and hands-on homework labs using TensorFlow, PyTorch, and Keras with OpenAI Gym environments.

## Use cases
- learn reinforcement learning from scratch
- find a practical RL course with coding assignments
- study deep reinforcement learning with pytorch
- self-study RL online for free
- practice RL algorithms on openai gym environments
- course materials for teaching reinforcement learning

## When to choose
- you want hands-on labs and homework rather than only theory
- you prefer a free, self-paced course runnable in Google Colab
- you want materials maintained for both English and Russian speakers

## When to avoid
- you need a production RL library rather than educational notebooks
- you want a formal certification or graded university credit
- you need cutting-edge research-level RL coverage beyond course scope

## Facets
- artifact type: learning-resource
- maturity: active
- function: reinforcement-learning, deep-learning, machine-learning
- domain: reinforcement-learning, tutorials, education, machine-learning
- platform: python, cross-platform
- tags: mooc, course-materials, jupyter-notebooks, openai-gym, tensorflow, pytorch, keras, hse, ysda

## Member repositories
- yandexdataschool/Practical_RL (main) score 57

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:45.257481+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 2026-08-29T17:43:41.269552+00:00, confidence not recorded.
  - readme: https://github.com/yandexdataschool/Practical_RL (fetched 2026-08-28T04:09:45.257481+00:00, sha 456097665acd)
- Data as of 2026-08-30T08:39:29.467469+00:00.