Data Science

Data science is a growing discipline aimed at equipping our students to enter a modern workforce that is increasingly data-driven. Converse’s data science minor prepares students to succeed in both the job market and graduate studies. From their first introductory course, students begin gaining skills in visualizing and analyzing data in programs such as Excel, Google Sheets, Tableau, R, and Python. Converse’s small student-to-faculty ratio allows for plenty of one-on-one faculty attention as students build their knowledge base.

Our introductory courses meet in the new Bank of America Data Analytics Learning Laboratory, which emphasizes a dynamic learning environment. Students will be actively engaged in labs and group projects in the classroom. This collaborative environment also fosters effective communication and presentation skills.

Bank of America Data Analytics Learning Laboratory: Converse’s Bank of America Data Analytics Learning Laboratory encourages classroom participation and active problem solving. The lab includes interactive platforms allowing students to share their work in real time with the instructor and fellow students. This dynamic learning environment encourages active learning, student involvement and collaboration in the education process.

Data Consulting: Spring 2020 students in Dr. Sorrells’ Quantitative Consulting class spent the semester working on industry-relevant problems from a partnering company, Bank of America, and were tasked with designing creative quantitative approaches to cybersecurity problems involving large sets of data.

This minor consists of core classes covering the fundamentals of gathering, cleaning, processing, analyzing, and inferring meaning from data sets. Students can complete the minor by taking data-driven courses that pair well with their major and career aspirations. Applications to business and science are emphasized, but the minor is useful to nearly any major.

Sample Courses

• Data Science I (MTH 117)
• Data Science II (MTH 118)
• Decision Analytics (ECN 304)
• Data for Business (CSC 208)

Minor Requirements:

Data Science I (MTH 117): 3 hours
Data Science II (MTH 118): 3 hours
Statistics (MTH 1113, MTH 423, ECN 300, BAD 300, PSY 311, or POL 303): 3 or 4 hours
Intro to Computer Programming (CSC 201): 4 hours
Two Electives: Approved by data science adviser: 6 hours

TOTAL: 19—20 hours

MTH 117 Course Description:
A first course in the study of data and the questions that can be answered by studying data. This course will also introduce students to R and Python to explore and visualize data effectively. Algorithms and basic modeling techniques will also be discussed.

MTH 118 Course Description:
A further study of data and the questions that can be answered by studying data. This course will introduce students to further programs and interfaces such as Maple and Weka. There will also be an emphasis on the entire process of collecting, processing, and understanding data before presenting results and limitations.

Electives: All elective courses counting toward the minor program should be selected with a mathematics or data science adviser. Examples of approved elective courses include Linear Algebra (MTH 351), Differential Equations (MTH 410), MTH 480 (for appropriate special topics), Decision Analytics (ECN 304), and Data for Business (CSC 208).

What are common careers in Data Science?

• Data Analyst
• Business Intelligence Analyst
• Strategy Analyst
• Healthcare Data Analyst
• Consultant
• Applications Architect
• Data Engineer
• Enterprise Architect
• Information Officer
• Database Manager
• Data Mining Analyst
• Data Visualization Developer