Undergraduate Degree Program in Data Science and Analytics, DSE concentration

Degree Requirements

The minimum number of credits required for the Bachelor of Science with major in Data Science and Analytics is 120 credits: 36 credits in the Intellectual Foundations (IFP) Program, 48 credits of major requirements and 36 credits of electives. Additional requirements:

A minimum of 45 upper-division credits;
Students must attain a minimum grade of "C" in all major courses to receive credit in the major; and
No major course may be taken with a pass/fail grade.

The 48 required credits for the major are listed below.

Common Core
Tools for Data Science	CAP 2751	3
Experimental Design and Data Analysis	CAP 2753	3
Artificial Intelligence for Social Good	CCJ 3071	3
Data Science Capstone*	ISC 4941	3
Mathematics for Data Science	MAP 2192	3
Data Management and Analysis with Excel	QMB 3302	3
Introductory Statistics	STA 2023	3
Common Core Credits		21

* The Capstone for the B.S. degree with major in Data Science and Analytics (ISC 4941) is a cross college course that can be taken multiple times with a minimum of 3 credits as a requirement for the degree. Students apply their theoretical knowledge, methods and tools acquired during the Data Science and Analytics program to a real-world problem and engage in processing data and applying appropriate analytic methods to the problem. Students implement a solution using appropriate tools and can work individually or in teams under the supervision of the course instructor or another faculty member. This can be accomplished in three ways: an approved Project, Research Experience or Written Thesis.

Concentration Core Requirements
Introduction to Data Science and Analytics	CAP 4773	3
Take all courses from either Group 1 or Group 2
Group 1
Introduction to Programming in C (if applicable**)	COP 2220	3
Foundations of Computer Science	COP 3014	3
Data Structures and Algorithm Analysis	COP 3530	3
Group 2
Introduction to Programming in Python	COP 3035	3
Data Structures and Algorithm Analysis with Python	COP 3410	3
*Concentration Core Credits*		*9 - 12*

Concentration Core Electives. Choose three courses or four courses so that the total of concentration credits is 21.
Introduction to Deep Learning	CAP 4613	3
Introduction to Artificial Intelligence	CAP 4630	3
Introduction to Data Mining and Machine Learning	CAP 4770	3
Introduction to Computer Systems Performance Evaluation	CEN 4400	3
Introduction to Database Structures	COP 3540	3
Introduction to Internet Computing	COP 3813	3
Python Programming	COP 4045	3
Applied Database Systems	COP 4703	3
*Concentration Elective Credits*		*9 - 12*
Concentration Credits		21

**Students who have taken a college-level introductory course in programming may substitute this course with one of the Concentration Elective Courses, with permission of the advisor.

Electives
Choose two courses from the Electives Table.
Elective Credits	6

Electives Table

*Arts and Letters Electives*
Research Methods in Bioarchaeology	ANT 4192	3
Information Technology in Public Administration	PAD 3712	3
Introduction to the Nonprofit Sector	PAD 4144	3
Quantitative Inquiry for Public Managers	PAD 4702	3
Research Methods for Public Management	PAD 4704	3
RI: Research Methods in Political Science	POS 3703	3
Public Opinion in American Politics	POS 4204	3
Sociological Analysis: Quantitative Methods	SYA 4400	3
*Business Electives*
Business Communication for Data Analysts	GEB 3231	3
Revenue Management and Predictive Analysis in the Hospitality and Tourism Industry	HFT 4481	3
Introduction to Business Analytics and Big Data	ISM 3116	3
Contemporary Issues of Digital Data Management	ISM 4041	3
Data Mining and Predictive Analytics	ISM 4117	3
Database Management Systems	ISM 4212	3
Management of Information Assurance and Security	ISM 4323	3
Advanced Business Analytics	ISM 4403	3
Social Media and Web Analytics	ISM 4420	3
Business Analytics for Marketing and Customer Relationship Management	MAR 4615	3
*Engineering Electives*
Introduction to Deep Learning	CAP 4613	3
Introduction to Artificial Intelligence	CAP 4630	3
Introduction to Data Mining and Machine Learning	CAP 4770	3
Introduction to Data Science and Analytics	CAP 4773	3
Introduction to Computer Systems Performance Evaluation	CEN 4400	3
Introduction to Database Structures	COP 3540	3
Introduction to Internet Computing	COP 3813	3
Python Programming	COP 4045	3
Applied Database Systems	COP 4703	3
*Science Electives*
Solar System Astronomy	AST 3110	3
Laboratory Methods in Biotechnology	BSC 4403L	3
Concepts in Bioinformatics	BSC 4434C	3
RI: Introduction to Data Science	CAP 3786	3
Cryptography and Information Security	CIS 4362	3
Spatial Data Analysis	GEO 4167C	3
Photogrammetry and Aerial Photograph Interpretation	GIS 4021C	3
Applications of Geographic Information Systems	GIS 4048C	3
Geospatial Databases	GIS 4118	3
Graph Theory	MAD 4301	3
Applied Mathematical Modeling	MAP 4103	3
RI: Industrial Problems in Applied Math	MAP 4913	3
Epidemiology of Infectious Diseases	MCB 4276	3
Topology for Data Science	MTG 4325	3
Practical Cell Neuroscience	PCB 4843C	3
Computational Physics	PHZ 3151C	3
Mathematical Methods for Physics	PHZ 4113	3
SAS for Data and Statistical Analyses	STA 3024	3
Computational Statistics	STA 3100	3
Introduction to Biostatistics	STA 3173	3
Applied Statistics 1 Lab	STA 4202L	1
Statistical Designs	STA 4222	3
Applied Statistics 1	STA 4234	2
Probability and Statistics 1	STA 4442	3
Probability and Statistics 2	STA 4443	3
Applied Statistics 2	STA 4702	3
Applied Time Series and Forecasting	STA 4853	3
*Social Work and Criminal Justice Electives*
Teen Technology Misuse	CCJ 4554	3
Methods of Research in Criminal Justice	CCJ 4700	3
Criminal Justice Technology	CJE 3692C	3
Crime Analysis	CJE 4663	3
Computer Crime	CJE 4668	3
Research Methods in Social Work	SOW 4403	3