machine-learning-zoomcamp/course.yaml at main · DataTalksClub/machine-learning-zoomcamp · GitHub

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schema_version: 2
content_id: deae4813-0ff6-4839-b6ed-bf6e1ea516bd
slug: ml-zoomcamp
title: Machine Learning Zoomcamp
current_cohort: "2026"
cohorts:
  - identifier: "2026"
    content: root
  - identifier: "2025"
    content: cohorts/2025
    legacy: true
  - identifier: "2024"
    content: cohorts/2024
    legacy: true
  - identifier: "2023"
    content: cohorts/2023
    legacy: true
  - identifier: "2022"
    content: cohorts/2022
    legacy: true
  - identifier: "2021"
    content: cohorts/2021
    legacy: true
description: |
  Machine Learning Zoomcamp is a free, hands-on course on machine learning
  engineering. Across its modules you work through regression, classification,
  model evaluation, tree-based models, and deep learning, then deploy what you
  build with FastAPI, Docker, AWS Lambda, and Kubernetes. A midterm project
  and a capstone project bookend the second half of the course.

  The course follows a project-first approach: theory is introduced as it is
  needed to solve real problems, with the focus on the practical engineering
  skills used in industry. All materials stay available for self-paced study
  between cohorts.
outcome: Build, evaluate, and deploy practical machine learning systems.
starting_point: You have programming experience and want to move into machine learning engineering.
prerequisites: You have at least one year of programming experience and are comfortable using the command line.
progression:
  - heading: I can program, but models still live in notebooks
    description: I want to move from experimenting with data to building machine learning systems that solve real problems.
  - heading: I turn data into evaluated models
    description: I practice regression, classification, model selection, deep learning, and the engineering around them.
  - heading: I deploy a practical machine learning system
    description: I package and publish a project that takes a model beyond the notebook and into an application.
urls:
  repository: https://github.com/DataTalksClub/machine-learning-zoomcamp
  docs: https://datatalks.club/docs/courses/ml-zoomcamp/
  faq: https://datatalks.club/faq/machine-learning-zoomcamp.html
hashtag: mlzoomcamp
published: true