Data Science Minor

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The minor in data science provides students with an introduction to data science. Students learn to extract meaning from data leveraging statistics, computer science, machine learning, and data engineering skills. That meaning is used to predict new outcomes, and to identify patterns that may not previously have been identified within the data. No previous knowledge of computing or statistics is required. The minor consists of three foundational courses and then three electives that range from software engineering to operations research, among others.

Minor Requirements

18 credits:

DATA 200 Introduction to Data Science (3)
DATA 210 Exploratory Data Analysis (3)
DATA 220 Machine Learning Models (3)

Choose three courses from the following list of electives:

CMSCI 120 - Introduction to Computer Science I Credits: (3)
CMSCI 125 - Introduction to Computer Science II Credits: (3)
CMSCI 254 - Data Structures and Algorithms Credits: (3)
CMSCI 349 - Software Engineering Credits: (3)
CMSCI 359 - Database Management Systems Credits: (3)
CMSCI 449 - Introduction to Artificial Intelligence Credits: (3)
DATA 201 - ST: Special Topics in Data Science Credits: (1) (May be taken 3 times.)
DATA 320 - Data Architecture Credits: (3)
DATA 330 - Data Wrangling Credits: (3)
DATA 340 - Advanced Data Visualization Credits: (3)
DATA 350 - Natural Language Processing Credits: (3)
DATA 410 - Advanced Machine Learning Credits: (3)
DATA 420 - High Performance Computing Credits: (3)
DATA 430 - Network Science Credits: (3)
MATH 228 - Discrete Mathematics Credits: (3)
MATH 247 - Calculus I Credits: (4)
MATH 332 - Graph Theory Credits: (3)
MATH 364 - Linear Algebra Credits: (3)
MATH 387 - Probability Credits: (3)
MATH 388 - Operations Research Credits: (3)
MATH 389 - Numerical Methods Credits: (3)
MATH 390 - Mathematical Statistics Credits: (3)
MATH 464 - Advanced Linear Algebra Credits: (3)
MATH 489 - Modeling and Simulation Credits: (3)
CMSCI 489 - Modeling and Simulation Credits: (3)
Alternately, students may choose two courses from the elective list and a statistical methods course from the following list:
ACCT 311 Forensic Accounting and Fraud Examination (3)
ACCT 312 Forensic Accounting and Litigation Advisory Services (3)
ACCT 413 Introduction to Forensic Data Analytics and Electronic Evidence (3)
BUS 250 Introduction to Business and Decision Making (3)
BUS 344 Operations and Supply Chain Management (3)
BUS 350 Marketing Research (3)
BIOL 205 Biostatistics (4)
ECON 211 Intermediate Macroeconomic Theory (3)
ECON 402 Applied Economic Analysis (3)
ECON 403 Econometrics (3)
PSCI 355 Political Research Methods and Analysis (4)
PSYCH 200 Research Methods and Statistics (3)
SOC 404 Statistics (4)

Note

Students minoring in Data Science and are majoring in a related major are allowed to double count three of the six courses. Students must take three courses that are not also counted for their major.