- Data Science
- Artificial Intelligence (AI)
- Machine Learning
- Predictive Analytics
- Modeling
- Artificial Neural Network
- Project Management
- Privacy
- Design Thinking
- Ethics
AI Product Management Specialization
Manage the Design & Development of ML Products. Understand how machine learning works and when and how it can be applied to solve problems. Learn to apply the data science process and best practices to lead machine learning projects, and how to develop human-centered AI products which ensure privacy and ethical standards.
Offered By
What you will learn
Identify when and how machine learning can applied to solve problems
Apply human-centered design practices to design AI product experiences that protect privacy and meet ethical standards
Lead machine learning projects using the data science process and best practices from industry
Identify and mitigate privacy and ethical risks in AI projects
Skills you will gain
About this Specialization
Applied Learning Project
L​earners will implement three projects throughout the course of this Specialization:
1​) In Course 1, you will complete a hands-on project where you will create a machine learning model to solve a simple problem (no coding necessary) and assess your model's performance.
2​) In Course 2, you will identify and frame a problem of interest, design a machine learning system which can help solve it, and begin the development of a project plan.
3​) In Course 3, you will perform a basic user experience design exercise for your ML-based solution and analyze the relevant ethical and privacy considerations of the project.
No programming experience or prior knowledge of machine learning / AI required.
No programming experience or prior knowledge of machine learning / AI required.
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
There are 3 Courses in this Specialization
Machine Learning Foundations for Product Managers
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.
Managing Machine Learning Projects
This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems. Participants will learn about the data science process and how to apply the process to organize ML efforts, as well as the key considerations and decisions in designing ML systems.
Human Factors in AI
This third and final course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the critical human factors in developing AI-based products. The course begins with an introduction to human-centered design and the unique elements of user experience design for AI products. Participants will then learn about the role of data privacy in AI systems, the challenges of designing ethical AI, and approaches to identify sources of bias and mitigate fairness issues. The course concludes with a comparison of human intelligence and artificial intelligence, and a discussion of the ways that AI can be used to both automate as well as assist human decision-making.
Offered by
Duke University
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
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