2024-2025 Academic Catalog

Dec 11, 2024

2024-2025 Academic Catalog

Data Science Minor

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Data Science Overview

Data is everywhere. Our increasingly global and digitized world produces massive amounts of data every day. Effectively managing and understanding data is essential to all organizations, whether they are in the public, private, or nonprofit arenas. Data science and analytics help organizations harness their data and use it to discover knowledge, identify opportunities, and develop solutions, ultimately leading to smarter policies, more efficient and equitable practices, better services, and more inclusive societies.

Clark University’s Data Science program provides a comprehensive interdisciplinary education that seamlessly integrates core data science, computer science, and mathematics courses with specialized domain knowledge. The program is supported by many dedicated faculty from diverse partner departments and schools, including Biology, Chemistry, Computer Science, Economics, Environmental Science, Geography, Interactive Media, Management, Mathematics, Psychology, Physics, and Sustainability and Social Justice.

We consider Data Science a multifaceted discipline that aligns well with the principles of liberal arts education. We emphasize critical thinking, problem-solving, creativity, communication, and team collaboration skills alongside technical proficiency; and help students develop these skills. In addition, Clark provides excellent opportunities for applying and further enhancing students’ knowledge and skills. At our program, undergraduates have opportunities to work as teaching assistants, research assistants, and participate in projects, competitions, and conferences, frequently under faculty guidance and with funding support.

Clark offers a large variety of academic programs and supports students to pursue their interests through combinations of majors and minors in their chosen fields. Furthermore, our student clubs and growing data science alumni community provide enrichment activities, mentoring and networking opportunities.

With our holistic curriculum, experiential learning, and supportive community, students acquire the knowledge, skills, and experiences needed to thrive in dynamic and data-driven industries, secure top-tier placements and unlock opportunities for advanced degrees. They are well prepared for making transformative changes in today’s data-rich world.

For more infomation and examples of student projects see the data science program website.

Minor Requirements

The Data Science Minor requires seven courses. Students must earn a course grade of C- or better in order to receive minor credit in Data Science. No course can be taken as pass/fail for the Data Science minor.

Foundational Math Courses

This one-year sequence should be completed as soon as possible. Any of these courses can be used to fulfill the formal analysis requirement. Students placed into pre-calculus should take that course as soon as possible and then continue to the 1-year Calculus sequence.

Foundational Computing Courses

CSCI 120 (for students with no prior CS background) or CSCI 124 (for students with prior CS background) should be taken as soon as possible. This is one of the prerequisites for intermediate data science courses such as DSCI 105 - Applied Data Analytics and DSCI 125 - Introduction to Data Science , along with a math prerequisite. CSCI 120 is also the prerequisite for CSCI 121 .

After CSCI 120 /CSCI 124 , the student may continue to DSCI 105 , DSCI 125 , or CSCI 121 , depending on the student’s interest, prerequisite status, and course offering.

Core Data Science Courses

Students must take the following courses:

DSCI 122 - Mathematical Foundations of Data Science

One of the following 100-level Data Science Courses:

One of the following 200-level Data Science Courses:

DSCI 122 should be taken as soon as possible, preferably immediately after completing Calculus II.

We highly recommend data science students to take both DSCI 105 and DSCI 125 , even though only one is required. These courses cover complementary materials that are crucial for both academic learning and career development in data science.

We also encourage students to take more than one 200-level core data science courses, even though only one is required for the minor. Please note that DSCI 216 and DSCI 225 have DSCI 122 , DSCI 105 or DSCI 125 , and CSCI 121 as prerequisites. DSCI 215 has GIS and computing courses as prerequisites. Data Science majors who are interested in taking DSCI 215 but don’t have all the GIS perquisites are encouraged to contact the DSCI 215 instructor for discussion and potential registration permission.

Data Science Faculty

Li Han, Ph.D., Director

Amir Aazami, Ph.D.

Charles Agosta, Ph.D.

Kenneth Basye, Ph.D.

Michael Boyer, Ph.D.

Mary-Ellen Boyle, Ph.D.

Paul Cotnoir, Ph.D.

Hamidreza Ahady Dolatsara, Ph.D.

Tim Downs, Ph.D.

Elliot Epstein, 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.

Arshad Kudrolli, Ph.D.

Ali Maalaoui, Ph.D.

John Magee, Ph.D.

Ranjan Mukhopadhyay, Ph.D

Gideon Maschler, Ph.D.

Tom Murphy, Ph.D.

Shuo Niu, Ph.D.

Olufemi Odegbile, Ph.D.

Alexander Petroff, Ph.D.

Gil Pontius. Ph.D.

Robert Ream, Ph.D.

Javier Tabima Restrepo, Ph.D.

John Rogan, Ph.D.

Morgan Ruelle, Ph.D.

Florencia Sangermano, Ph.D.

Barbara Capogrosso Sansone, Ph.D.

Michael Satz, M.S.

Inshik Seol, Ph.D.

Peter Story, Ph.D.

Natalia Sternberg, Ph.D.

Andrew Stewart, Ph.D.

Zhengyang Tang, Ph.D.

Terrasa Ulm, Ph.D.

Catalin Veghes, M.S.

Edouard Wemy, Ph.D.

Christopher Williams, Ph.D.

Jing Zhang, Ph.D.

Junfu Zhang, Ph.D.