MLOps (machine learning operations) is becoming a must-know skill for many data professionals. Master the fundamentals of MLOps, from training and experimentation to deployment and monitoring.
Join Slack • #course-mlops-zoomcamp Channel • Telegram Announcements • Course Playlist • FAQ • Tweet about the Course
- Start Date: May 2025
- Register Here: Sign up
- Stay Updated: Subscribe to our Google Calendar (Desktop only)
All course materials are freely available for independent study. Follow these steps:
- Watch the course videos.
- Join the Slack community.
- Refer to the FAQ document for guidance.
The course consists of structured modules, hands-on workshops, and a final project to reinforce your learning. Each module introduces core MLOps concepts and tools.
To get the most out of this course, you should have prior experience with:
- Python
- Docker
- Command line basics
- Machine learning (e.g., through ML Zoomcamp)
- 1+ year of programming experience
- What is MLOps?
- MLOps maturity model
- NY Taxi dataset (our running example)
- Why MLOps is essential
- Course structure & environment setup
- Homework
- Introduction to experiment tracking
- MLflow basics
- Model saving and loading
- Model registry
- Hands-on MLflow exercises
- Homework
- Workflow orchestration
- Using Mage for ML pipelines
- Homework
- Deployment strategies: online (web, streaming) vs. offline (batch)
- Deploying with Flask (web service)
- Streaming deployment with AWS Kinesis & Lambda
- Batch scoring for offline processing
- Homework
- Monitoring ML-based services
- Web service monitoring with Prometheus, Evidently, and Grafana
- Batch job monitoring with Prefect, MongoDB, and Evidently
- Homework
- Unit and integration testing
- Linting, formatting, and pre-commit hooks
- CI/CD with GitHub Actions
- Infrastructure as Code (Terraform)
- Homework
- End-to-end project integrating all course concepts
Join the #course-mlops-zoomcamp channel on DataTalks.Club Slack for discussions, troubleshooting, and networking.
To keep discussions organized:
- Follow our guidelines when posting questions.
- Review the community guidelines.
- Cristian Martinez
- Tommy Dang
- Alexey Grigorev
- Emeli Dral
- Sejal Vaidya
- Machine Learning Zoomcamp – 4-month ML Engineering course
- Data Engineering Zoomcamp – 9-week Data Engineering course
- LLM Zoomcamp
- Stock Market Analytics Zoomcamp
How can I prepare for the course?
- If you’re new to Flask or Docker, check out:
- ML Zoomcamp: Module 5
- Docker section from Data Engineering Zoomcamp
- If you’re new to machine learning, start with:
- ML Zoomcamp: Module 1 for an overview
- Module 3 for Scikit-Learn basics (used in this course)
- Module 6 for XGBoost (optional but helpful)
I registered but didn’t receive an invite. Is this normal? Yes, invites aren’t automated. You’ll receive an email eventually.
To stay updated:
- Join the
#course-mlops-zoomcampchannel on Slack - Subscribe to our YouTube channel
A special thanks to our course sponsors for making this initiative possible!
Interested in supporting our community? Reach out to [email protected].
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