Data Science Minor

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 that you may obtain from the CSE Department office.

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 348 Predictive Analytics in Business (3)

ECO 247 Sabermetrics (3)

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

CSE 327 Artificial Intelligence Theory and Practice (3)

CSE 337 Reinforcement Learning (3)

CSE 345 WWW Search Engines (3)

CSE 375 Principles of Practice of Parallel Computing (3)

ISE 111 Engineering Probability (3)

ISE 121 Applied Engineering Statistics (3)

ISE 224 Information Systems Analysis and Design (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)

PSYC 110 Statistical Analysis of Behavioral Data (4)

PSYC 210 Experimental Research Methods and Laboratory (4)

BIS 324 Business Data Management (3)

ECO 245 Statistical Methods II (3)

ECO 357 Econometrics (3)

ECO 367 Applied Microeconometrics (3)

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.

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