Data Science (DSCI) - BS Major

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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)

A minimum of 12 credits at 300-level or above with same prefix (ex: BIOL, ECON, FIN) chosen in consultation with academic advisor. DSCI, STAT, and CS courses cannot be used.

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 330 - Management of Unstructured Data (3 credits)
DSCI 415 - Unsupervised Learning (3 credits)
◎ DSCI 425 - Supervised Learning (3 credits)
DSCI 430 - Data Science at Scale (3 credits)

Choose one:

◆ CS 341 - Data Structures (4 credits)
CS 368 - Introduction to Bioinformatics (4 credits)
DSCI 330 - Management of Unstructured Data (3 credits)
DSCI 415 - Unsupervised Learning (3 credits)
◎ DSCI 425 - Supervised Learning (3 credits)
DSCI 430 - Data Science at Scale (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

✪ = Civic Engagement and Service Learning