Program: Data Science Minor - Clark University

Data Science Overview

Data Science, broadly speaking, develops techniques for distilling knowledge and information out of empirical data. It is a dynamic, newly emerging field that combines techniques from Statistics, Mathematics, and Computer Science. It has applications particularly relevant to Clark’s programs in Economics, Business Analytics, GIS, IDCE, Biology, Chemistry, and Physics, although it can also interact with the quantitative aspects of any discipline. Nationwide, Data Science is emerging as an important and popular area of study with excellent employment prospects.

The Data Science major and minor at Clark aim at providing a solid education to students and preparing students for graduate study, and/or careers in industry and non-profits. With our curriculum and our teaching we pursue the following goals:

Develop in students a solid foundation of data-centered computing and the ability to learn on their own;
Develop in students a good understanding of the key statistics and computational concepts, principles, and techniques;
Develop in students a broad range of practical skills required of data science professionals , such as formulating problems, designing data collection strategies, processing and analyzing data, extracting information from the data, and using the information to make sound decisions;
Develop in students a general understanding of the social issues surrounding data science and the code of conduct in this discipline;
Develop in students an appreciation and desire for knowledge and life-long learning;
Foster creativity, independence, discipline, responsibility, respect, and ethical behavior.

Minor Requirements

A minor in Data Science consists of five to seven courses, depending on whether students take the one year sequence of the foundational mathematics and computer science courses or the one semester Honors course. Students must earn a minimum course grade of C- in order to receive minor credit in Data Science. No course can be taken as pass/fail for the Data Science minor.

Data Science Minor Requirements:

Math Courses

Computer Science Courses

Data Science Courses

DSCI 122 - Mathematical Foundations of Data Science
DSCI 125 - Introduction to Data Science or DSCI 105 - Applied Data Analytics
One 200-level Data Science Course
- DSCI 216 - Stochastic Computing
- DSCI 225 - Applied Machine Learning

If a student is interested in earning both the Data Science (DS) minor and the Actuarial and Financial Mathematics minor, each minor must contain at least 3 unique courses. This requirement may cause some AFM minor students to have to take an additional computer science or data science course in order to also complete the data science minor. The Data Science program will approve relevant extra courses on an as-needed basis.

Data Science Faculty

Li Han, Ph.D., Director

Amir Aazami, Ph.D.

Kenneth Basye, Ph.D.

Mary-Ellen Boyle, Ph.D.

Tim Downs, Ph.D.

Lyndon Estes, Ph.D.

Jackie Geoghegan, Ph.D.

Frederic Green, Ph.D.

Yelena Ogneva-Himmelberger, Ph.D.

Gary Holness, Ph.D.

Minji Jung, Ph.D.

Aghil Alaee Khangha, Ph.D.

Ali Maalaoui, Ph.D.

John Magee, Ph.D.

Gideon Maschler, Ph.D.

Tom Murphy, Ph.D.

Shuo Niu, Ph.D.

Olufemi Odegbile, Ph.D.

Gil Pontius. Ph.D.

Robert Ream, Ph.D.

Morgan Ruelle, Ph.D.

Michael Satz, M.S.

Inshik Seol, Ph.D.

Peter Story, Ph.D.

Natalia Sternberg, Ph.D.

Zhengyang Tang, Ph.D.

Catalin Veghas, M.S.

Edouard Wemy, Ph.D.

Jing Zhang, Ph.D.

Junfu Zhang, Ph.D.

Data Science Minor

Data Science Overview

Minor Requirements

Data Science Faculty

Data Science Core Courses