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Machine Learning Foundations for Product Managers

Course Cover

5

(8)

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Course Features

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Duration

16 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

16 hours

Course Description

The Pratt School of Engineering, Duke University offers the first course of their AI Product Management Specialization. This course will provide a solid understanding about machine learning and how it works. To manage an AI product/team, you will need to be able collaborate with engineers, data scientists, customers, and other machine-learning professionals. This course is a non-coding introduction to machine learning. This course will cover the development of models, model evaluation, and interpretation. It also covers intuition behind common ML algorithms. It will allow you to train and optimize a machine-learning algorithm for real-world problems.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

N​o prior knowledge of machine learning or programming experience required

What You Will Learn

Explain how machine learning works and the types of machine learning

Describe the challenges of modeling and strategies to overcome them

Identify the primary algorithms used for common ML tasks and their use cases

Explain deep learning and its strengths and challenges relative to other forms of machine learning

Implement best practices in evaluating and interpreting ML models

Course Instructors

Jon Reifschneider

Director, Master of Engineering in AI for Product Innovation, Duke University

Jon Reifschneider is the Director of Masters Studies for the Artificial Intelligence for Product Innovation (AIPI) program in Duke University's Pratt School of Engineering. Prior to joining the Duke ...

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