Data Science (DSCI) - BS Major

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$DSCI Program Image$

60-62 credits (no minor required)

2.0 GPA required.

Letter grade required in all major courses unless otherwise noted.

The discipline of data science focuses on transforming data into knowledge. This degree requires a student to acquire knowledge and expertise in data science through an understanding of analytical and computational techniques, an interdisciplinary emphasis, and a capstone experience.

Data Science Major Map

Required Courses (51-52 credits)

Interdisciplinary Emphasis (12 credits)

Choose 12 credits at 300-level or above with the same prefix (ex: BIOL, ECON, FIN). Different prefixes with a common theme may be allowed with advisor approval.

Capstone Experience (6 credits)

◎ DSCI 395 - Professional Skill Development for Data Sciences (2 credits)
◎ DSCI 495 - Communication of Capstone Outcomes (1 credit)

Project/Internship - choose one:

A project or internship proposal must be developed in consultation with academic advisor.

DSCI 488 - Data Science Project (1-6 credits)
DSCI 492 - Internship in Data Science (1-6 credits)

Electives (9-10 credits)

Choose two:

DSCI 326 - Data Science at Scale (3 credits)
DSCI 330 - Management of Unstructured Data (3 credits)
DSCI 415 - Unsupervised Learning (3 credits)
DSCI 425 - Supervised Learning (3 credits)

Choose one:

◆ CS 341 - Data Structures (4 credits)
CS 368 - Introduction to Bioinformatics (4 credits)
◎ CS 447 - Machine Learning (3 credits)
DSCI 326 - Data Science at Scale (3 credits)
DSCI 330 - Management of Unstructured Data (3 credits)
DSCI 415 - Unsupervised Learning (3 credits)
DSCI 425 - Supervised Learning (3 credits)
STAT 335 - Principles of Study Design (3 credits)
◎ STAT 370 - Statistical Consulting and Communication (3 credits)

Legend

◎ = Oral Intensive

◆ = Math/Critical Analysis Intensive

△ = Writing Intensive

✽ = Physical Development and Wellness Graduation Requirement