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What is this?
A free 9-week course from DataTalks.Club that teaches MLOps fundamentals — productionizing machine learning services, from training and experimentation to deployment and monitoring.
A free 9-week course from DataTalks.Club that teaches MLOps fundamentals — productionizing machine learning services, from training and experimentation to deployment and monitoring.Is it just videos, or is there hands-on work?Video lectures (a YouTube playlist) plus hands-on work: each module has workshops and homework, materials live in this GitHub repo, and the course ends with a final project.
Video lectures (a YouTube playlist) plus hands-on work: each module has workshops and homework, materials live in this GitHub repo, and the course ends with a final project.How do I actually take it — are there live classes?No live classes: lectures are pre-recorded. Right now the way in is self-paced — follow the materials on GitHub, ask questions in the #course-mlops-zoomcamp Slack channel, do the self-checked homework, and build a project for your portfolio.
No live classes: lectures are pre-recorded. Right now the way in is self-paced — follow the materials on GitHub, ask questions in the #course-mlops-zoomcamp Slack channel, do the self-checked homework, and build a project for your portfolio.Do I need prior ML experience to keep up?Yes — you should know Python, Docker, and command-line basics, have machine learning experience (for example from ML Zoomcamp), and about a year of programming overall.
Yes — you should know Python, Docker, and command-line basics, have machine learning experience (for example from ML Zoomcamp), and about a year of programming overall.Can I still earn a certificate?Not in self-paced mode: certificates are awarded only to learners who complete the final project during a live cohort, and none is planned for 2026. Self-paced learners also miss the leaderboard and peer review.
Not in self-paced mode: certificates are awarded only to learners who complete the final project during a live cohort, and none is planned for 2026. Self-paced learners also miss the leaderboard and peer review.I'm a data scientist — is this built for me, or for engineers?Both: it targets data scientists, ML engineers, and software engineers who want to put machine learning models into production and operate them reliably.
Both: it targets data scientists, ML engineers, and software engineers who want to put machine learning models into production and operate them reliably.What tools will I get hands-on with?MLflow for experiment tracking and the model registry, workflow orchestration, Flask web services, AWS Kinesis and Lambda for streaming, Prometheus, Evidently, and Grafana for monitoring, MongoDB for batch jobs, plus GitHub Actions and Terraform in the best-practices module.
MLflow for experiment tracking and the model registry, workflow orchestration, Flask web services, AWS Kinesis and Lambda for streaming, Prometheus, Evidently, and Grafana for monitoring, MongoDB for batch jobs, plus GitHub Actions and Terraform in the best-practices module.What is the final project?It integrates everything covered in the course into an end-to-end MLOps pipeline that you build yourself — the portfolio piece of the course.
It integrates everything covered in the course into an end-to-end MLOps pipeline that you build yourself — the portfolio piece of the course.What dataset does the course use?The NY Taxi dataset is the running example used throughout the course.
The NY Taxi dataset is the running example used throughout the course.Is it really free?Yes. All videos, materials, and homework are free and open-source, in both live and self-paced formats.
Yes. All videos, materials, and homework are free and open-source, in both live and self-paced formats.What are similar projects?machine-learning-zoomcamp, AI-Engineering-Lab, DevOps-Roadmap, dive-into-machine-learning, TensorFlow-Course, Made-With-ML, numerical-linear-algebra, kedro
machine-learning-zoomcamp, AI-Engineering-Lab, DevOps-Roadmap, dive-into-machine-learning, TensorFlow-Course, Made-With-ML, numerical-linear-algebra, kedroWhich topics is it in?workflow-orchestration, tracking, flask, grafana, mlops, prometheus, ci-cd, aws, deployment, curriculum, course, github-actions
workflow-orchestration, tracking, flask, grafana, mlops, prometheus, ci-cd, aws, deployment, curriculum, course, github-actions