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Learner Reviews & Feedback for Machine Learning Foundations for Product Managers by Duke University

4.6
stars
57 ratings
15 reviews

About the Course

In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology. This course provides a non-coding introduction to machine learning, with focus on the process of developing models, ML model evaluation and interpretation, and the intuition behind common ML and deep learning algorithms. The course will conclude with a hands-on project in which you will have a chance to train and optimize a machine learning model on a simple real-world problem. At the conclusion of this course, you should be able to: 1) Explain how machine learning works and the types of machine learning 2) Describe the challenges of modeling and strategies to overcome them 3) Identify the primary algorithms used for common ML tasks and their use cases 4) Explain deep learning and its strengths and challenges relative to other forms of machine learning 5) Implement best practices in evaluating and interpreting ML models...

Top reviews

WM

Jan 9, 2022

A very good introduction to ML Jon Reifschneider explains very well the topics with real-world experience\n\n-based on this professional experience.

SV

Nov 29, 2021

Really a good introduction to Machine Learning, it helps you to boost your interest on the field and create a product from zero!

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1 - 16 of 16 Reviews for Machine Learning Foundations for Product Managers

By Jun W T

Dec 18, 2021

A very clear introduction to the 'types' of Artificial Intelligence and other necessary concepts required in dealing with AI.

By Wolf Z

May 9, 2022

It is a good introduction into machine learning concepts that finds the right balance between required depth and and time efficient knowledge transfer.

As the title indicates, it is a good introduction on management level and is not suited to train data scientists.

A negative point: The instructor speaks incredibly slow and is rather unenthusiastic. However putting the speed on 1.5-2 times fixes this.

By Justine R

Mar 17, 2022

I love the way the course is structured. Jon Reifschneider allows you to view and download the slides before diving into the videos. He explains the content thoroughly and supports his explainations with charts and diagrams which I personally find very helpful. I'm so glad I took the time to complete this course.

By Jose A B

Jun 9, 2022

I rarely leave comments but this is legit o​ne of the best courses I've taken on Coursera. It's clear enough to be accessible to beginners yet offers sufficient information to allow more-intermediate learners take assignments further. Really good, for real.

By Wilberto M

Jan 10, 2022

A very good introduction to ML Jon Reifschneider explains very well the topics with real-world experience

-based on this professional experience.

By Sofía P V

Nov 30, 2021

Really a good introduction to Machine Learning, it helps you to boost your interest on the field and create a product from zero!

By John P

Apr 25, 2022

G​reat course. Clear, informative, and cited numerous real-world examples to help learners grasp seemingly abstract concepts.

By Nancy

Jan 18, 2022

Very good courses that clearly and precisely covered the foundation concepts for machine leaning!

By Pankaj

Mar 3, 2022

Great content, Knowledgeable Instructor, well explained.

Course has been helpful , Thanks!

By Richard S

Jun 16, 2022

Vey interesting and enjoyable to undertake

By B S P

Mar 7, 2022

Very practical to apply

By Ali A

Mar 26, 2022

Very useful, indeed.

By Gaytri B

Jan 24, 2022

Good KT

By Andrei K

Mar 16, 2022

The training provides a good overview of ML concepts. At the same time pre-project data quality review and initial data analysis could have a more extensive coverage from my point of view

By Ramanan K

Feb 21, 2022

A lot of good content, but not a great presentation/organization making it hard to be engaging. Especially for working professionals, the presenter's energy level does not motivate them to keep going. You are better off doing a proper AI/ML course instead.

By Amr

Jan 28, 2022

t​he instructor is reading from a slide,it is not a well prepared course