https://github.com/artefactory/xhec-mlops-2025

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X HEC MLOps crashcourse 2025

README

# Overview

## Objective

Teach practical aspects of productionizing ML services — from collecting requirements to model deployment and monitoring.

## [MANDATORY] Pre-requisites & setup

> [!Note]
> TL; DR
>
> - Docker Desktop
> - Git
> - Python 3.11
> - UV
> - Install requirements

You can find all pre-requisites and setup instructions [here](PREREQUISITES.md).

## Timeline

Course start: October 21st
Course end: October 24th

## Syllabus

## [Module 1: Introduction to MLOps](lessons/00-intro)

- What is MLOps
- Course overview
- Coding best practices
- Prerequisites and setup
- Running example: NY Taxi trips dataset

## [Module 2: Experiment Tracking](lessons/01-model-and-experiment-management)

- Experiment tracking intro
- What is MLflow
- Experiment tracking with MLflow
- Saving and loading models with MLflow
- Model registry
- Practice

## [Module 3: Model Deployment](lessons/02-model-deployment)

- Web service: model deployment with FastAPI
- Docker: containerizing a web service
- Practice

## [Module 4: Pipelines and Orchestration](lessons/03-pipeline-and-orchestration)

- Tasks, Flows, Deployments
- From notebooks to Workflows
- Workflows orchestration with prefect
- Practice

## Project

- End-to-end project with all the things above

## Instructors

- DEBES Hugo
- JOUINI Youssef
- ROHART Capucine
- SION Pierre