Data science is an interdisciplinary field of study that focuses on understanding, processing, interpreting, visualizing, and communicating data.
The minor comprises three core courses (a statistics course from any department, DS 256, and DS 325), and three electives.
- One course in statistics
- DS 256 Data Science Programming
- DS 325 Applied Data Science
- Three electives
|Course Number||Course Title||Prerequisites|
|BIO 260||Biostatistics||Bio 112|
|ECON 241||Introductory Economics and Business Statistics||ECON 103 and 104, and one of the following: Math 105-106, 111 or equivalent; or department permission|
|HS 232||Statistics for Health Sciences||None|
|MATH 107||Applied Statistics||None|
|MATH 353||Probability and Statistics||Math 211 & Math 212 with a C- or better|
|MGT 235||Statistical Methods||None|
|POL 215||Methods of Political Science||Completion of Pol 101, 102, 103, or 104 and sophomore status or above|
|PSYCH 205||Introduction to Statistics||PSYCH 101 and Psychology major|
|SOC 299||Data Analysis and Statistics||1 100-level Sociology course and 1 200-level Sociology course|
DS 256 Data Science Programming
Data scientists apply methods from statistics, data analysis, computer science, and machine learning in order to gain insight from data. In Data Science Programming, we focus on developing the programming and machine learning skills necessary to gain such insight. Through experiential learning, we equip students with the fundamental computer problem-solving skills and tools to clean raw data, engineer data features, build statistical and machine learning models, predict unknown values and/or discern patterns, and present data insights. No prerequisites.
DS 325 Applied Data Science
Advanced treatment of data science concepts. Through a series of case studies, students explore datasets from a variety of domains and extract meaningful information and insights using mathematical, computational, and other scientific methods and algorithms. Topics include the fundamental algorithms of data science: regression, decision trees, support vector machines, clustering, and neural networks. Through a semester-long project, students demonstrate knowledge of fundamental data science concepts and ability to interpret and communicate effectively the results of the analysis. Prerequisites: DS 256: Data Science Programming and an approved statistics course.
Students must take three approved elective courses. At least one elective must be taken outside the student’s major department(s), and only one elective can be at the 100-level. One possible elective is the newly approved DS 150 Data Science and Society, but we offer many other courses that fulfill the elective requirement.
DS 150: Data Science and Society
This course introduces students to data science and research design. This course is divided into two parts. During the first half of the semester, students will be introduced to theories of science and how systematic and falsifiable analysis applies to a wide variety of fields of study. During the second half of the semester, students will be introduced to data management, statistical and computer programming software, and econometrics.
|Course Number||Course Title||Prerequisites|
|ARTS 160||Introduction to Digital Media||None|
|BIO 251/CS 251||Introduction to Bioinformatics||BIO 112|
|BIO 315||Molecular and Genome Evolution||BIO 211|
|CS 360||Principles of Database Systems||CS 216|
|CS 371||Introduction to Artificial Intelligence||CS 216|
|DS 150||Data Science and Society||None|
|DS 220||Cultural Analytics||Any 100-level course in SOC or CIMS; MUS_CLAS-213; OR any 200-level course in ENG or foreign languages and literatures; OR any gateway course for area, ethnic, group, or global studies majors (e.g. LAS 145).|
|ECON 350||Econometrics||ECON 241, 243, and 245|
|ECON 352||Advanced Econometrics||ECON 350, plus one other 300-level ECON course|
|ES 230||Introduction to Geographic Information Systems||ES 196 or permission of instructor|
|ES 363||Remote Sensing||ES 230 or permission of instructor|
|FYS 162||Math and Voting||First year students only|
|MATH 342||Applied Linear Algebra||MATH 212 with a C- or better|
|MATH 353*||Probability and Statistics||MATH 211 and MATH 212 with a C- or better|
|MATH 362||Operations Research||None|
|MATH 363||Wavelets and Their Applications||MATH 212 with a C- or better|
|MGT 301||Research Methods||MGT 235|
|MGT 303||Systems Thinking||MGT 235 and MGT 275|
|MGT 321||Topics in Operations Management||MGT 235 or declared business minor that has completed statistics requirement|
|MGT 395||Organizational Ethics||Jr or Sr status|
|PHIL 109||Wrong Science, Bad Science, Pseudo Science||None|
|PHIL 211||Logic||100 level philosophy course or permission of instructor|
|PHIL 253||Philosophy of Technology||100 level philosophy course or permission of instructor|
|PHYS 335||Computational Methods in Physics||Jr or Sr status and instructor permission|
|PHYS 350||Observational Astronomy||PHYS 211, PHYS 110, or instructor permission|
|PSYCH 305||Experimental Methods||PSYCH 205|
* For the Data Science Minor, Math 353 can count as either the Statistics course or as an elective. It cannot count as both.
Elective Courses through Affiliated Study Abroad Programs
Many off campus study programs offer courses that meet DS minor requirements, including:
- Lancaster University, England offers a variety of undergraduate courses in data science across several departments.
- CET Shanghai, China offers a full undergraduate program of courses and internship opportunities in data science.
- DIS in Copenhagen, Denmark offers several courses that would support the Data Science minor including Computational Analysis of Big Data and Econometrics.
- American University in Cairo, Egypt offers a BSc in Data Science and a full curriculum taught in English.