# 3. Orchestration and ML Pipelines

## [3.0 Introduction: ML pipelines and Mage](3.0/README.md)

## [3.1 Data preparation: ETL and feature engineering](3.1/README.md)

## [3.2 Training: sklearn models and XGBoost](3.2/README.md)

## [3.3 Observability: Monitoring and alerting](3.3/README.md)

## [3.4 Triggering: Inference and retraining](3.4/README.md)

## [3.5 Deploying: Running operations in production](3.5/README.md)

## [3.6 Homework](../cohorts/2024/03-orchestration/homework.md).

## Quickstart

See the [Unit 3.0](https://github.com/DataTalksClub/mlops-zoomcamp/blob/main/03-orchestration/3.0/README.md) for a Quick Start guide

## Need help?

1. [Developer documentation](https://docs.mage.ai/introduction/overview)
1. [AI chat bot](https://mageai.slack.com/archives/C05NYC4DADT)
1. Live chat with the [Mage team directly](https://mage.ai/chat)


## Notes

Did you take notes? Add them here:

* [Marcus' Notes for Ch3](https://github.com/mleiwe/mlops-zoomcamp/blob/Ch3_ML_Notes/cohorts/2024/03-orchestration/ML_Notes.md)
* Send a PR, add your notes above this line

### Notes previous editions

- [2022 Prefect notes](../cohorts/2022/03-orchestration/README.md)
- [2023 Prefect notes](../cohorts/2023/03-orchestration/prefect/README.md)