The final course, Machine Learning for Higher Education: Advanced Applications, deepens learners’ understanding of state-of-the-art machine learning architectures including ensemble methods and advanced machine learning techniques and models. Participants work on a capstone project to design, implement, and present advanced machine learning solutions for complex higher ed challenges. With a focus on real-world student success metrics like retention, GPA, and progression, participants gain hands-on experience preparing complex datasets, tuning hyperparameters, and interpreting results for meaningful impact on their own institution’s data systems.

The course concludes with a capstone project, giving learners the opportunity to design, implement, and present an advanced applied machine learning solution for higher education.

Upon completion of this course, students receive a micro-credential that can be stacked with Course 1: Applied Data Analytics For Higher Education and Course 2: Machine Learning for Higher Education: Applied Foundations to satisfy requirements for the full Applied Analytics and Machine Learning for Higher Education Certificate.