Requirements of Minor
The five-course sequence will provide students with innovative analytical tools to approach problems and will improve their marketability — regardless of their major.
1) Elements of Computing I
Introduction to programming for students without prior programming experience. Programming structures suitable for basic computation. Elements of computer organization and networking. Development of programming skills including data manipulation, multimedia programming, and networking. Standards for exchange and presentation of data. Comprehensive programming experience using Python.
2) Introduction to Data Science
MDSC 20009/SOC 20009
This course will orient students to the field, to key concepts, to the types of questions addressed, to the technical aspects of data science and to the process of making sense of data. Provides an overview from both a computer science, natural science, humanities and social science perspectives. Prerequisite: CSE 10101
MDSC students are required to take a statistics class. The minor accepts the following classes: SOC30903 “Statistics for Sociological Research”, ECON30330, “Statistics for Economics”, Math30540 “Mathematical Statistics”, Psy30100 “Experimental Psychology I: Statistics”, ACMS20340 “Statistics for Life Sciences”, ACMS30440 “Probability and Statistics”, ACMS30600 “Statistical Methods and Data Analysis”, ITAO 20200/BAMG 20150 “Statistical Inference in Business”, POLS 40810 "Quantitative Political Analysis."
If students are using the same statistics course to fulfill both the MDSC requirement and a college, university, major or other minor requirement, they must contact their dean or major advisor to see if an additional course (not another statistics course) is required or if the course can be double counted.
Students may petition to have other statistics courses accepted to fulfill the requirement, by contacting Mim Thomas (email@example.com).
Although MDSC accepts several statistics courses to fulfill the minor, the following two statistics courses have seats set aside specifically for MDSC students.
4 & 5) Two Topical Electives
Electives chosen from a wide variety of disciplines, including network analysis, data visualization, and machine learning. May include courses specific to students’ majors.
“The data science minor will offer students across the University the opportunity to understand the role of data generally as well as in their field of study, and to employ confidently the latest techniques that transform data into insights.”
—Patrick Flynn, professor and chair of the Department of Computer Science and Engineering