DataTalks.Club's Free ML Zoomcamp Hits 14,600 Stars and Opens 2026 Registration
DataTalks.Club's free four-month course on production ML engineering has crossed 14.6k stars, covering everything from regression to Kubernetes serving.
- DataTalks.Club's free ML Zoomcamp hits 14.6k stars, 2026 cohort starts September 14
- Four-month course covers regression, classification, trees, deep learning, and deployment
- Stack: scikit-learn, PyTorch, TensorFlow, FastAPI, Docker, Kubernetes, AWS Lambda
- Certificate requires two end-to-end projects plus peer reviews during the live cohort
- Prerequisites are one year of programming and command-line comfort, no prior ML needed
- Materials are free and self-paced anytime via the YouTube playlist
DataTalks.Club’s free, community-run Machine Learning Zoomcamp has returned to GitHub Trending after its repository passed 14,600 stars. Registration is open for the 2026 cohort, which starts September 14 and covers the path from a raw dataset to a containerized prediction service running on Kubernetes.
The curriculum follows trained models into deployment. Learners evaluate models, expose predictions through an HTTP API, package the application with Docker, and deploy it using serverless or container orchestration tools. That production focus addresses the work required to move a model out of a notebook and connect it to other software.
GitHub stars track interest in the repository. The public lessons, assignments, project criteria, and deployment examples make the course’s scope available for inspection before registration.
From notebook to running service
Python anchors the course, with NumPy and pandas for data preparation, scikit-learn for classical machine learning, and TensorFlow, PyTorch, and Keras for neural networks. The deployment modules introduce FastAPI, Docker, AWS Lambda, Kubernetes, TensorFlow Serving, and KServe.
| Stage | Topics and tools | Practical output |
|---|---|---|
| Problem framing |
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