DATA SCIENCE & ENGINEERING

Prerequisites & course information

Requisites: MATH 112 , 114 , 171, or member of Engineering Guest Students Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Repeatable for Credit: No Last Taught: Fall 2025 Learning Outcomes: 1. Write working code in Python to import, manipulate, analyze, visualize, and otherwise interact with datasets of various types. Audience: Undergraduate 2. Perform descriptive analyses to extract, summarize, and interpret salient features from datasets. Audience: Undergraduate 3. Perform predictive analyses to model trends and make predictions from datasets. Audience: Undergraduate 4. Apply techniques to identify and clean data that contains missing entries, outliers, or other forms of noise or uncertainty. Audience: Undergraduate 5. Recognize and evaluate potential issues pertaining to bias, fairness, privacy, and ethics in applying data science techniques. Audience: Undergraduate Learning Outcomes: 1. Write working code in Python to import, manipulate, analyze, visualize, and otherwise interact with datasets of various types. Audience: Undergraduate 2. Perform descriptive analyses to extract, summarize, and interpret salient features from datasets. Audience: Undergraduate 3. Perform predictive analyses to model trends and make predictions from datasets. Audience: Undergraduate 4. Apply techniques to identify and clean data that contains missing entries, outliers, or other forms of noise or uncertainty. Audience: Undergraduate 5. Recognize and evaluate potential issues pertaining to bias, fairness, privacy, and ethics in applying data science techniques. Audience: Undergraduate