SDS 250 - Advanced Data Science

3 Credit(s)

This course provides an in-depth exploration of advanced data science techniques, including clustering, principal component analysis (PCA), and neural networks. Students will learn to apply these methods to real-world data sets, uncovering patterns, reducing dimensionality, and building predictive models. Emphasis is placed on practical applications and developing an intuitive understanding of complex algorithms. Through hands-on projects, students will gain experience with tools and programming languages commonly used in data science, equipping them with the skills needed to solve sophisticated data challenges across diverse fields.

When Offered: Spring semester.
Prerequisite(s): SMA 129 Business Statistics and Data Analytics or SMA 127 Scientific Statistics; SCS 142 Programming II: Math & Engineering
Writing Intensive Course