# MLOps

Taking machine learning systems to production: reproducibility, automation, deployment, and
monitoring.

**Prerequisites:** the [Machine Learning](/en/Machine%20Learning) course, basic command line and Git.

## Syllabus

1. [Introduction](/en/MLOps/01%20Introduction)
2. The ML Lifecycle *(planned)*
3. Experiment Tracking *(planned)*
4. Data and Model Versioning *(planned)*
5. Pipelines and Automation *(planned)*
6. Model Deployment *(planned)*
7. Monitoring and Observability *(planned)*

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