0 or 3 credits
Spring 2026 Lecture Laboratory Upper Division
In the past decade, we have observed the expeditious evolution and tremendous applications of machine learning, such as unmanned vehicle, autonomous language translation, and smart healthcare. This course will introduce both the fundamental knowledge and design/application insights of machine learning techniques via a series of hands-on real-world examples. The overall aim is to provide the students with a good understanding of machine learning technologies, building machine learning models, and applying machine-learning technologies to address real-world problems. In this course, students will also have an opportunity to explore the cutting-edge machine learning technologies, such as deep learning, adversarial attacks, and meta learning, and develop their own machine learning-based solutions.
Learning Outcomes1Demonstrate both the fundamental knowledge and design/application insights of the state-of-the-art machine learning techniques.
2Implement machine learning models.
3Apply machine learning techniques to solve real-world problems.
Prerequisites
Restrictions
made by Purdue students.