This course is part of the AI Product Management Specialization

4.6
stars
140 ratings

Jon Reifschneider

13,363 already enrolled

Offered By

AI Product Management SpecializationDuke University

About this Course

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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

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Course 1 of 3 in the

AI Product Management Specialization

Beginner Level

No prior knowledge of machine learning or programming experience required

Approx. 15 hours to complete

English

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Skills you will gain

Data Science
Artificial Neural Network
Machine Learning
Predictive Analytics
Modeling

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 1 of 3 in the

AI Product Management Specialization

Beginner Level

No prior knowledge of machine learning or programming experience required

Approx. 15 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.65/5 (62 Ratings)

Jon Reifschneider

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

Engineering

15,522 Learners

3 Courses

Offered by

Duke University

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Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

What is Machine Learning

2 hours to complete

10 videos (Total 47 min), 2 readings, 1 quiz

Week2

Week 2

2 hours to complete

The Modeling Process

2 hours to complete

8 videos (Total 40 min), 1 reading, 1 quiz

Week3

Week 3

2 hours to complete

Evaluating & Interpreting Models

2 hours to complete

8 videos (Total 34 min), 1 reading, 1 quiz

Week4

Week 4

2 hours to complete

Linear Models

2 hours to complete

6 videos (Total 33 min), 1 reading, 1 quiz

Reviews

4.6

41 reviews

5 stars
78.01%
4 stars
15.60%
3 stars
2.12%
2 stars
1.41%
1 star
2.83%

TOP REVIEWS FROM MACHINE LEARNING FOUNDATIONS FOR PRODUCT MANAGERS

by NNJan 17, 2022

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

by JPApr 24, 2022

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

by VKSep 25, 2022

One of the best course to understand the basics with accuracy

by DPNov 13, 2022

Very good but also very technical. Refresh your math :-)

View all reviews

About the AI Product Management Specialization

Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems. This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects.

This Specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems. Learners will build skills in applying the data science process and industry best practices to lead machine learning projects, and develop competency in designing human-centered AI products which ensure privacy and ethical standards. The courses in this Specialization focus on the intuition behind these technologies, with no programming required, and merge theory with practical information including best practices from industry. Professionals and aspiring professionals from a diverse range of industries and functions, including product managers and product owners, engineering team leaders, executives, analysts and others will find this program valuable.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Machine Learning Foundations for Product Managers

About this Course

Skills you will gain