datatalksclub/mlops-zoomcamp

This repository hosts MLOps Zoomcamp, a free nine-week course from DataTalks.Club that teaches how to take a machine learning model from a notebook to a running service. MLOps stands for machine learning operations, the practice of training, deploying, and watching over ML models in production. The course covers training and experimentation, deployment, and monitoring. The README notes that the team does not plan to run the course in 2026 but the materials are still available for self-paced learning. To work through it on your own, you watch the course videos, join the DataTalks.Club Slack workspace, and consult the linked FAQ. There is an Airtable form to register interest if the course is ever offered again. The course expects some background. Listed prerequisites are Python, Docker, basic command line, prior machine learning exposure such as the team's ML Zoomcamp, and at least one year of programming experience. The structure is six modules followed by a final project. Module 1 introduces MLOps, the MLOps maturity model, and the NY Taxi dataset that runs through the lessons. Module 2 covers experiment tracking and model management with MLflow, including saving and loading models and using a model registry. Module 3 looks at workflow orchestration and ML pipelines. Module 4 deals with model deployment, contrasting online deployment (web services and streaming) with offline batch scoring, with hands-on work using Flask for a web service and AWS Kinesis plus Lambda for streaming. Module 5 covers monitoring of ML services, using Prometheus, Evidently, and Grafana for web services and Prefect, MongoDB, and Evidently for batch jobs. Module 6 walks through software engineering practices such as unit and integration tests, linting and formatting with pre-commit hooks, CI and CD with GitHub Actions, and infrastructure as code with Terraform. The final project ties the modules together in one end-to-end build. Support is provided through the #course-mlops-zoomcamp channel on the DataTalks.Club Slack, with links to question-asking guidelines and community rules. The instructors are Cristian Martinez, Alexey Grigorev, and Emeli Dral. The README also describes DataTalks.Club itself, a global online community of data practitioners that runs events, free courses, and a newsletter, with most day-to-day discussion happening in Slack.