Data Science, BS

The foundations of the Bachelor of Science in Data Science are data curation, mathematical foundations, computational thinking, statistical thinking, data modeling, communication and visualization, and ethics.

Degree Requirements, Admission, Policies, Tuition & Fees, Calendar

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Program Learning Outcomes

Students who complete this major will learn the data cycle of obtaining, curating, managing, processing, exploring, analyzing, and communicating data. They will:

Connect abstract mathematics with real-world problems involving data.
Apply computational and statistical thinking to the acquisition and analysis of data.
Build statistical models and assess them.
Become proficient in current statistical, numerical, and visualization software.
Responsibly handle data.
Communicate their analyses in both written and visual formats.

Major Requirements: 52 credits

CS 150 - Introduction to Computer Science I 4 credit(s)
CS 250 - Introduction to Computer Science II 4 credit(s)
CS 445 - Introduction to Database Systems 4 credit(s)
DSCI 340 - Algorithms & Data Structures 4 credit(s)
DSCI 407 - Statistical Modeling and Regression 4 credit(s)
DSCI 440 - Machine Learning and Data Mining 4 credit(s)
DSCI 490 - Senior Capstone 2 credit(s)
DSCI 492 - Senior Capstone II 2 credit(s)
MATH 206 - Computational Linear Algebra 4 credit(s)
MATH 226 - Calculus I 4 credit(s)
MATH 227 - Calculus II 4 credit(s)
MATH 307 - Calculus-Based Statistics 4 credit(s)
MEDA 319 - Information Design 2 credit(s)
PHIL 202 - Ethics and Society 4 credit(s)
SCI 280 - Technical Writing in Science 2 credit(s)