Students will explore data-driven mathematical models to find solutions to complex problems, using techniques collectively known as Machine Learning. Topics include both supervised learning (parametric and nonparametric algorithms, vector solutions. and neural networks) and unsupervised learning (clustering, dimensionality reduction, and deep learning). Prior programming experience with Python or R is required. Basic understanding of linear algebra is helpful but not required. Prerequisite: MAT 2108 Introduction to Data Science or MAT 2110 Principles of Computer Science with Python.
- Teacher: Holly Rosson