Data Science

Data Science

Are you interested in working with quantitative and qualitative data to solve real-world problems? Do you enjoy collaborating with others and communicating your findings clearly?

Data Science involves study a range of topics related to working with quantitative and qualitative data to solve real-world problems. This interdisciplinary major includes coursework in mathematics, computer science, as well as specialized courses that focus on analyzing and interpreting data.

Hanover’s data science program combines relevant coursework from Mathematics and Computer Science with a distinct introductory course (DS110) and a senior thesis requirement (DS471) to provide a successful Data Science experience at the undergraduate level. You’ll learn how to write computer code to analyze large data sets, ask interesting questions, evaluate claims, draw inferences, and effectively communicate data-driven answers to real-world problems.

Data Science Requirements

Interested students are advised to begin their program of study in their first year by taking Calculus I (MAT121) and Introduction to Data Science (DS110). Students are advised to consult with a member of the Data Science faculty to plan a four-year course of study as early as possible, as several of the required courses are only offered every second year.

Our faculty members are all experts in Data Science and are here to guide you throughout your four-year program of study. They’ll help you plan your courses, offer advice on career paths and assist you with your senior thesis.

WHAT DO DATA SCIENCE MAJORS STUDY?

  • Data Analysis
  • Data Mining
  • Machine Learning
  • Statistical Inference
  • And other topics that interest you

COURSES

Number
Name
Units
Description

DSCI 110 Introduction to Data Science 1.00 Teaches critical concepts and skills in applied statistics and computer programming, in conjunction with hands-on analysis of real-world datasets such as economic data, document collections, geographical data, and social network data. Includes discussion of social issues surrounding data analysis such as privacy and data ethics. Emphasis on concrete examples and active learning. Prerequisite: MAT 101 or MAT 113 or MAT 121 (or above), or placement at the Ready for Precalculus level (or above). Partially satisfies the SM CCR. Satisfies the QL ACE.Partially satisfies the SM CCR. Satisfies the QL ACE.

Faculty

Haris Skiadas Professor of Mathematics and Computer Science 812-866-6190 skiadas@hanover.edu

Kevin Stormer '04 Chief Information Officer 812-866-6839 stormer@hanover.edu

Barbara Wahl Professor of Mathematics & Computer Science 812-866-7326 wahl@hanover.edu

Theresa Wilson Assistant Professor of Computer Science 812-866-6189 wilsont@hanover.edu

Bradley Burdick Visiting Instructor of Mathematics 812-866-7343 burdick@hanover.edu

Carl Jagels Professor of Mathematics and Computer Science 812-866-6186 jagels@hanover.edu

Yefim Katsov Professor of Mathematics 812-866-6119 katsov@hanover.edu

Duong Nguyen Assistant Professor of Mathematics 812-866-7343 nguyen@hanover.edu

Haris Skiadas Professor of Mathematics and Computer Science 812-866-6190 skiadas@hanover.edu

Jeffrey Vaughn vaughnj@hanover.edu

Barbara Wahl Professor of Mathematics & Computer Science 812-866-7326 wahl@hanover.edu