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DATA - Data Science

General Program Information

Program Title

Data Science

College

CAS

Department(s)

Math, Computer Sci, & Data Sci

Program Level

UG

Program Type

MAJOR

Degree Designation

BS

Data Science, B.S.

Students majoring in Data Science will develop skills in data analytics as well as the programming skills necessary for creating and managing databases and working with extremely large data sets.  There are opportunities for interested students to do data science research with faculty, and internship opportunities in the region are abundant.

In order to remain in the program, students who have declared the major in Data Science must maintain satisfactory progress toward completion of the major by completing DATA 200 Intermediate Data Science with a grade of C- or higher by the end of the second year and completing DATA 260 Intermediate Statistics with a grade of C- by the end of the fall semester of the third year.

Students may not earn both the major in Data Science and the minor in Statistics and Analytics.

Program Learning Goals for Data Science

  1. Data Acquisition: Students will collect, store, preserve, manage, and share data in a distributed environment through practical, hands-on experience with programming languages and big data tools.

  2. Problem Exploration: Students will develop problem-solving skills through experiences that foster computational and data analytic thinking.

  3. Analysis: Students will develop an in-depth understanding of the key technologies in data science: data mining, machine learning, visualization techniques, predictive modeling, and statistics.

  4. Domain knowledge: Students will experience discipline-specific data use cases in order to solve real-world problems of high complexity.

  5. Interpretation: Students will learn methods for effective data communication and visualization, and demonstrate their use in data representation.

  6. Social Value: Students will explore social and ethical implications of the use of data and technology.

Major Requirements

Required Courses

CS 128

INTRODUCTION TO SOFTWARE APPLICATION DEVELOPMENT

3

CS 128L

INTRODUCTION TO SOFTWARE APPLICATION DEVELOPMENT LABORATORY

1

DATA 100

INTRODUCTION TO DATA SCIENCE

3

DATA 122

ELEMENTARY STATISTICS

3

DATA 150

DATABASE SYSTEMS

3

DATA 200

INTERMEDIATE DATA SCIENCE

3

DATA 260

INTERMEDIATE STATISTICS WITH SPSS

3

DATA 300

ADVANCED DATA SCIENCE

3

DATA 424

REGRESSION ANALYSIS

3

DATA 470

DATA SCIENCE PROJECT

3

Alternatives to DATA 122 are: DATA 228, EC 210, or PO 105. CS 129 is an alternative to CS 128 + CS 128L.

DATA Electives

Two DATA courses at the 300 level or above.

Application Area Courses

Two courses (6 credits) chosen from this list:

BI 200

DATA-DRIVEN DECISION-MAKING

3

BI 341

ADVANCED DATA-DRIVEN DECISION-MAKING

3

BI 371

BUSINESS DECISION OPTIMIZATION

3

COM 369

SOCIAL MEDIA STRATEGY & ANALYTICS

3

COM 373

SPORTS PROMOTION & FAN ENGAGEMENT

3

EPA 412

EXERCISE TESTING AND PRESCRIPTION I

3

ER 304

SOCIAL ENTREPRENEURSHIP

3

PO 203

POLITICS & MAPPING

3

PO 205

HEALTHCARE ACCESS IN LATIN AMERICA

2

PO 302

QUANTITATIVE RESEARCH METHODS

3

PS 301

EXPERIMENTAL DESIGN AND ANALYSIS IN PSYCHOLOGY

4

PS 401

ADVANCED RESEARCH METHODS IN PSYCHOLOGY

3

PS 435

TESTS AND MEASUREMENTS

3

SC 350

SOCIOLOGICAL RESEARCH METHODS I

3

SC 351

SOCIOLOGICAL DATA ANALYSIS

3

Students may submit an academic petition for an application area course that is not on this list.

Students are responsible for completing any pre- or co-requisites for the courses on this list.

Additional Electives

Two courses, chosen from:

  • DATA course at the 300 level or above

  • The list of application area courses above

  • Theoretical foundation courses

    • MT 242

    • MT 421

Total Credit Hours: 46