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Machine Learning Foundations for Product Managers
This course is part of AI Product Management.
Course Cost
Free course
Intermediate
Skill Level
12 Hours
Self-paced Video lessons
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full AI Product Management Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
43,916 Enrolled
English
What you'll learn
Explain machine learning concepts and types
Describe modeling challenges and solutions
Identify key algorithms for common ML tasks
Understand deep learning fundamentals
Implement ML model evaluation best practices
Develop AI product management strategies
Skills you'll gain
This course includes:
4.4 Hours PreRecorded video
6 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 6 modules in this course
This comprehensive course provides product managers with essential knowledge of machine learning fundamentals. The curriculum covers the entire ML lifecycle, from data preparation to model deployment, focusing on practical applications without requiring coding skills. Students learn about different types of machine learning, model evaluation techniques, and real-world implementation strategies. The course includes hands-on projects and emphasizes best practices in AI product management.
What is Machine Learning
Module 1 · 1 Hours to complete
The Modeling Process
Module 2 · 1 Hours to complete
Evaluating & Interpreting Models
Module 3 · 1 Hours to complete
Linear Models
Module 4 · 1 Hours to complete
Trees, Ensemble Models and Clustering
Module 5 · 1 Hours to complete
Deep Learning & Course Project
Module 6 · 6 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: AI Product Management
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.8
55
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56,564
Students
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Courses
Jon Reifschneider is the Director of the Master of Engineering in Artificial Intelligence for Product Innovation (AIPI) program at Duke University's Pratt School of Engineering, where he also teaches graduate courses in machine learning. With a robust background in data services and analytics, Jon previously held senior management roles for 15 years, most notably as Senior Vice President at DTN, where he led the Weather Analytics division. His team developed predictive analytics systems that have become integral to the operations of major transportation, aviation, and energy utility organizations across the United States and globally. Jon's academic credentials include a B.S. in Mechanical Engineering from the University of Virginia, a Master of Engineering Management from Duke University, an M.S. in Analytics from Georgia Tech, and a Global MBA from EBS in Germany. His international experience spans the U.S., Luxembourg, Germany, and India, enriching his perspective on global engineering challenges. As a leader in integrating AI with product innovation, Jon Reifschneider is committed to advancing education and research in this dynamic field.
Frequently asked Questions
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