MATH-4002 Introduction to Data Science
This course introduces the principles, methods, and mindset of modern data science for advanced undergraduates. Students learn to acquire, clean, explore, visualize, and model data using reproducible workflows and programming tools. Emphasis is placed on understanding uncertainty, communicating results, and evaluating models in applied contexts. Topics include data wrangling, exploratory data analysis, statistical inference, predictive modeling, and ethical considerations in data-driven decision making. This course is intended for senior-level students in mathematics, computer science, business, or the sciences who are seeking a capstone-level introduction to applied data science methods. It is expected that all students will be comfortable coding in either R or Python.