machine-learning-zoomcamp is a free 4-month open-source course covering the entire machine learning engineering pipeline, from building models with Python to deploying them in production. It is designed for learners with at least one year of prior programming experience.
Project overview
It addresses the lack of accessible, structured, end-to-end ML engineering training by providing a complete pipeline curriculum at no cost, spanning fundamentals through containerized and serverless deployment.
Project type
Learning Resources
Use cases
Learning & Education
Deployment
Refer to project documentation
License
License pending
Best for
Developers with 1+ year of programming experience who want structured, end-to-end training in ML engineering from fundamentals through production deployment
Key capabilities
Course modules teaching fundamentals, CRISP-DM, linear regression, feature engineering, and regularization using Python and scikit-learn.
Course modules on logistic regression, feature selection, decision trees, ensembles, and evaluation metrics including ROC AUC and F1-score.
Course module introducing neural networks using TensorFlow, Keras, and PyTorch, including CNNs and transfer learning.
Course modules covering model serialization, building FastAPI web services, Docker containerization, AWS Lambda serverless deployment, and Kubernetes scaling.
Limitations and risks
The course takes 4 months to complete as a live cohort.
Requires 1+ year of prior programming experience, making it inaccessible to those without coding backgrounds.
Getting started
Follow the materials on GitHub or register for the live cohort for free. Ask questions in Slack, do the homework, and build a project.