Machine Learning Fundamentals for Product Managers

In this first course in the AI ​​Product Management Specialization offered by the Duke University Pratt School of Engineering, you'll gain a fundamental understanding of what machine learning is, how it works, and when and why it's used. To successfully manage an AI team or product and collaborate with data scientists, software engineers, and customers, you'll need to understand the fundamentals of machine learning technology. This course is a non-coding introduction to machine learning, focusing on the model development process, evaluating and interpreting ML models, and the intuition behind common ML and deep learning algorithms. The course culminates in a hands-on project where you'll have the opportunity to train and optimize a machine learning model on a simple, real-world problem. By the end of this course, you should be able to: 1) Explain how machine learning works and the different types of machine learning 2) Describe modeling challenges and strategies for overcoming them 3) Identify the main algorithms used to solve common machine learning problems and examples of their application 4) Explain deep learning and its advantages and challenges compared to other forms of machine learning 5) Apply best practices for evaluating and interpreting machine learning models