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Learner Reviews & Feedback for Managing Machine Learning Projects by Duke University

4.8
stars
377 ratings

About the Course

This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems. Participants will learn about the data science process and how to apply the process to organize ML efforts, as well as the key considerations and decisions in designing ML systems. At the conclusion of this course, you should be able to: 1) Identify opportunities to apply ML to solve problems for users 2) Apply the data science process to organize ML projects 3) Evaluate the key technology decisions to make in ML system design 4) Lead ML projects from ideation through production using best practices...

Top reviews

DM

May 4, 2026

Clear understanding of the different problems on how to approach ML opportunities

JI

Jul 10, 2024

I like this course; it is very informative. I learned a lot of useful concepts, and I reinforced much of what I knew. I recommend this course, even if is just for fun.

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101 - 103 of 103 Reviews for Managing Machine Learning Projects

By Subash C S

•

May 22, 2025

Very nice

By 21PCT09 M

•

Sep 29, 2025

Nice

By Ronnie B

•

Apr 21, 2026

as an actual product manager, not a programmer or someone aspiring to be a programmer, I found this course utterly useless. there wasn't any information in it that could be even generously describe as relevant for PMs, and ALL of the best practices mentioned could be simply be summarised by "don't be an idiot!" if this was the first course in the specialisation, I would have NEVER made it even halfway through!