Machine Learning Foundations for Product Managers

 

Build your subject-matter expertise

This course is part of the AI Product Management Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate

Join Free: Machine Learning Foundations for Product Managers

There are 6 modules in this 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