MLOps Practitioner
Learn proper MLOps practices and how to implement them
Level
Duration
Role
Advanced
4h minimum
Advanced Data Analyst, Data Engineer, Data Scientist, ML Engineer
You’ll be able to:
- Recognize and avoid pitfalls while preparing projects and ML models for production
- Identify refactoring and documentation techniques before deploying to production
- Perform batch deployment, monitor, and update projects on the Automation node
- Design, deploy, and monitor API services
- Take the MLOps Practitioner certification
Recommended Courses to Prepare for Certification
Optional Courses to Go Beyond
Production Concepts
What is involved in MLOps and how can I get prepared? Find out by starting here on your MLOps journey!
60 min
Preparing for Production
Discover what automation, optimization, and documentation tasks should be applied before deploying your project to production.
45 min
Projects in Production
Learn how to batch deploy projects to a production environment.
60 min
Real-time APIs
Learn how to deploy predictive models for real-time scoring using the Dataiku API node.
75 min
Dataiku Govern
Learn how to use Dataiku Govern for AI project and model management.
45 min