Module 4 · MLOps: Deploying Machine Learning & Deep Learning Models

ML Pipelines and CI/CD: lessons

Experiment tracking, model registries, and automated pipelines from raw data to a released model.

3 lessons · 47 min

What this module teaches, what it asks of you first and how you practise it are on its syllabus page.

Experiment Tracking and the Model Registry
16 min
Logging every run's parameters, metrics and artefacts automatically, then promoting a model to production through a registry — not by overwriting a file.
Included with the track Simulation inside
Training Pipelines
16 min
Six repeatable steps from raw data to a validated model — and why data validation and preprocessing inside the model are the parts that save you.
Included with the track Simulation inside
CI/CD for Machine Learning
15 min
Testing code, data and model behaviour before every release — and a gate that compares the challenger with the champion on a frozen test set.
Included with the track

Experiment Tracking and the Model Registry