PSCI 4501 - Science Informatics Capstone

1-3 Credit(s) | $13.50 per credit Fee

In this course students will demonstrate proficiency in developing machine learning models and applying data science techniques on real-world scientific datasets. Jupyter notebooks will be used to generate, present, and annotate code. Additionally, students will learn to evaluate the output of models for predictive analysis and optimize models based on real-world feedback. Skills in preparing scientific reports and visualizations based on the output of models will also be developed. (As Needed) [Graded Letter]

Prerequisite(s): PHYS 2501 - Prerequisite Min. Grade: C
Repeatable for Add’l Credit? Yes - Total Credits: 6