Sign in
Free Advanced MLOps

Full Stack Deep Learning

Taking models from notebook to production.

Most courses stop at the model. This one starts where they stop: how to set up a project, manage the data, deploy the thing, and keep it working once real traffic hits it.

UC Berkeley with UC Berkeley

Listed by AI Review Rating. We are not affiliated with UC Berkeley and earn nothing from this link.

Full Stack Deep Learning

Course overview

Published by the Full Stack team out of UC Berkeley, it is aimed at people who can already train a model and now have to ship one.

What you will learn

  • Set up a deep learning project so it stays reproducible
  • Manage, label and version data as a first-class part of the system
  • Test and troubleshoot models before they reach production
  • Deploy a model and monitor what happens to it afterwards

Who this course is for

ML engineers you can train a model and now have to run one
Product teams shipping AI the operational half nobody taught you

Course details

FormatRecorded lectures, labs and project work
LevelAdvanced
PriceFree
Time30 hours
CertificateNo certificate

About UC Berkeley

UC Berkeley logo

The Full Stack team, out of UC Berkeley, teaches the operational half of machine learning: project setup, data management, deployment and monitoring, for people who can already train a model.

Learner ratings

No ratings yet. We publish an average once 3 members have rated it, so one opinion never reads as a score.

Taken this course? Sign in or create a free account to rate it. Ratings are members-only so one person cannot set the average.

More courses like this