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. By completing this course, participants earn a stackable micro-credential that, alongside the previous two courses, fulfills requirements for the Applied Analytics and Machine Learning for Higher Education Certificate.