MAT-235 Introduction to Data Science

Apply standards and practices for collecting, organizing, managing, and exploring data, combining principles and skills from statistics and computer programming with a goal of using these tools to provide information to decision makers. Topics include causality, single and multivariable data manipulation, data visualization and generation, statistical inference, statistical modeling, and machine learning. prerequisite: A grade of C or better in any college level math course, or CTP-160 Python, or permission from the Mathematics Assistant Dean. In addition to these course requirements, students must possess proficiency in basic computing tasks, including file storage and management and online communications.

Term: Spring 2026

Course Type: Credit - 4 Credits

Section: 001

Ways to take the class: Hybrid

Days: MW

Time: 12:30PM to 2:00PM

Start Date: 01/21/2026

End Date: 05/17/2026

Location: Arnold Campus

Room: MATH 206 Building:
Math/Child Development Center

Instructor: TBA (Subject to change)

Class Size: 20

General Education Requirement: Mathematics

Section Info: This is a hybrid section with in-person meetings Mondays and Wendesdays from 12:30 - 2:00pm, along with an online component. Exams for this section may require in-person testing at a testing center. For additional information, visit: https://www.aacc.edu/resources/academic- services/testing/testing-for-existing- students/