The computational analysis of data, both large and small, has become essential to academic and industrial institutions. The minor in Data Science provides an overview of data science as well as familiarity with its interdisciplinary statistical and computational foundations to understand, build and use computational tools to analyze data. The minor is open to undergraduates from all colleges.

The minor is comprised of three required courses, one applied data mining / analytics course at the 200 or 300 level, and one or more approved electives relating to data science. See course requirements in catalog description below.

A grade of C or better is required of all minor courses.

Virtually every discipline collects data to gain a deeper understanding of their discipline and to make better decisions. The technical challenges associated with collecting, storing, processing, communicating, visualizing, analyzing, and interpreting the huge quantities of data that have become available today are far from trivial. The courses of the minor in Data Science help prepare students to develop computational solutions to analyze data and provide insights of value.

To declare the minor, fill out the form linked at the bottom of this page.

The minor is open to undergraduates from all colleges, and requires a minimum of 16 credit hours, consisting of the following:


Three required courses (10-11 credits):

CSE 160 Introduction to Data Science (3)

CSE 017 Programming and Data Structures (3) OR CSE 109 Systems Software (4)

MATH 312 Statistical Computing and Applications (4)

Total Credits 10-11


One approved applied data mining / analytics course at the 200/300 level (3 credits):

CSE 326 Fundamentals of Machine Learning (3)

CSE 347 Data Mining (3)

ISE 364 Introduction to Machine Learning (3)

ISE 367 Mining of Large Datasets (3)

MKT 325 Consumer Insights through Data Analysis (3)

MKT 326 Marketing Analytics in a Digital Space (3)

BIS 352 Advanced Topics in Business Analytics (3) or BUAN 352 Predictive Analytics in Business (3)**

ECO 325 (MKT 325) Consumer Insights through Data Analysis (3)

ECO 360 Time Series Analysis (3)

The director may approve additional applied data mining / analytics courses.


One or more approved electives related to data science including, but not limited to an additional applied data mining/analytics course from above, or the following (3-4 credits)

CSE 241 Database Systems and Applications (3)

CSE/BIOE 320 Biomedical Image Computing (3)**

CSE 323 Computer Vision** (this course is being offered in Spring 2024 as CSE 398-018/498-018)

CSE 325 Natural Language Processing (3)**

CSE 327 Artificial Intelligence Theory and Practice (3)

CSE 337 Reinforcement Learning (3)

CSE 341 Database Systems, Algorithms, and Applications (3)

CSE 345 WWW Search Engines (3)

CSE 349 Big Data Analytics (3)**

CSE 360 Introduction to Mobile Robotics (3)**

CSE 371 Principles of Mobile Computing (3)**

CSE 375 Principles of Practice of Parallel Computing (3)

ACCT 330 Accounting Data and Analytics (3)**

BIS 324 Business Data Management (3) (only for business majors)

BUAN 348 Predictive Analytics in Business (3) or BIS 348 Predictive Analytics in Business (3) (only for business majors)

BUAN 357 Artificial Intelligence for Business (3)**

COMM 165 Data Storytelling (4)**

ECE 303 Accelerated Computing for Deep Learning (3)**

ECE 340 Introduction to Online and Reinforcement Learning (3)**

ECE 344 Statistical Signal Processing (3)**

ECO 357 Econometrics (3)

ECO 367 Applied Microeconometrics (3)

ISE 111 Engineering Probability (3)

ISE 121 Applied Engineering Statistics (3)

ISE 224 Information Systems Analysis and Design (3)

ISE 365 Applied Data Mining (3)**

MATH 043 Survey of Linear Algebra (3)

MATH 205 Linear Methods (3)

MATH 242 Linear Algebra (3-4)

STAT 342 Linear Algebra (3)

MATH 309 Theory of Probability (3)

MATH 334 Mathematical Statistics (3,4)

MATH 338 Linear Models in Statistics with Applications (3,4)**

MATH 365 Statistical Machine Learning (3,4)**

POLS 322 The Politics of Data (4)**

PSYC 201 Research Methods and Data Analysis I (4)

PSYC 202 Research Methods and Data Analysis II (4)


The program director may approve additional data science-related electives.

Many of the courses that apply to the minor have prerequisites. These prerequisites do not count toward the minor, and students attempting to complete the minor are not recused from these prerequisites.

** These courses are regularly approved but not may show up in the catalog yet. You will need to submit a degree program exception for these courses.


Data Science Minor Form

Questions about the minor may be addressed to the director, Prof. Aparna Bharati.