Data Science and Data Analytics, Emphasis in Data Science, BS

Data science and data analytics applications exist in numerous industries and government agencies. This diversity of opportunity is reflected in the interdisciplinary nature of the Data Science and Data Analytics (DSDA) Program which involves six colleges; Agriculture, Education and Behavioral Science, Engineering and Computer Science, Liberal Arts and Communication, Nursing and Health Professions, and Sciences and Mathematics. The DSDA Program builds out from the general education curriculum to a program core of 37 hours and two specific emphasis areas from which students can choose. The program core is required of all students in the program and covers content in Statistics, programming, visualization, data governance and ethics. The two emphases - Data Science and Data Analytics - provide further depth beyond the program core. Within each emphasis, students will be required to complete courses within their particular area of interest or “domain”. Domains could include social sciences, healthcare, geospatial technologies, engineering, computer science or other application areas. Each emphasis (including the domain study) will require 45-46 hours.

The domain studies, proposed by participating colleges, will conform to the following parameters:

All courses proposed as part of domain studies will have to be existing courses or courses proposed as part of other academic programs in the university
Domain studies affiliated with the Data Science emphasis are limited to 21 to 22 hours of which 7 hours are upper level.
Domain studies affiliated with the Data Analytics emphasis are limited to 32 to 34 hours of which 10 hours are upper level.

The outcomes of the BS program are:

Identify societal and ethical impacts as well as the responsibility that come with access to data.
Critically assess and remediate issues with data organization and data quality.
Design and implement a solution to a problem in the realm of data science/data analytics through problem identification, problem solving, decision making, visualization, data analysis and reporting.

A 19-hour undergraduate certificate in Data Analytics is also available to all majors. The outcomes of the certificate are:

Identify societal and ethical impacts as well as the responsibilities that come with access to data.
Critically assess and remediate issues with data organization and data quality.

A complete 8-semester degree plan is available at https://www.astate.edu/info/academics/degrees/

University Requirements:

See University General Requirements for Baccalaureate degrees

First Year Making Connections Course:

CS 1093 - Making Connections Computer Science Sem. Hrs: 3
OR
MATH 1093 - Making Connections Mathematics Sem. Hrs: 3
OR
First Year Making Connections course aligned to Domain Study option Sem. Hrs: 2-3

General Education Requirements:

See General Education Curriculum for Baccalaureate Degrees Sem. Hrs: 35

Students with this major must take the following:

COMS 1203 - Oral Communication Sem. Hrs: 3
MATH 1023 - College Algebra Sem. Hrs: 3 or MATH course that requires MATH 1023 as a prerequisite
PHIL 1103 - Introduction to Philosophy Sem. Hrs: 3

Major Requirements (Program Core):

GIS 3503 - Geospatial Data Applications Sem. Hrs: 3
CS 1114 - Concepts of Programming Sem. Hrs: 4
DATA 2004 - Programming for Data Analysis Sem. Hrs: 4
DATA 3003 - Applied Database and Data Mining Sem. Hrs: 3
DATA 3011 - Data Science and Analytics Seminar Sem. Hrs: 1
DATA 3023 - Data Visualization and Data Communication Sem. Hrs: 3
DATA 303V - Internship for Data Science and Data Analytics Sem. Hrs: Variable
DATA 4003 - Fundamental Concepts in Design of Experiments Sem. Hrs: 3
DATA 4013 - Data Science and Data Analytics Capstone Sem. Hrs: 3
PHIL 3723 - Computers, Ethics, and Society Sem. Hrs: 3
STAT 3133 - Applied Categorical Data Analysis Sem. Hrs: 3
STAT 3233 - Applied Statistics I Sem. Hrs: 3
STAT 3243 - Regression Analysis and Analysis of Variance (ANOVA) Sem. Hrs: 3

Sub-total: 37

Emphasis Area (Data Science):

CS 4623 - Fundamentals of Data Science Sem. Hrs: 3
CSED 4231 - Principles of Operating Systems Sem. Hrs: 1
CSED 4241 - Principles of Computer Organization Sem. Hrs: 1
CSED 4731 - Principles of Abstract Structures Sem. Hrs: 1
MATH 1054 - Precalculus Mathematics Sem. Hrs: 4
MATH 2183 - Discrete Structures Sem. Hrs: 3
MATH 2204 - Calculus I Sem. Hrs: 4
MATH 2214 - Calculus II Sem. Hrs: 4
MATH 3243 - Linear Algebra Sem. Hrs: 3

Sub-total: 24

Domain Studies (Data Science Emphasis):

Domain Studies of 21 or 22 hours of which seven hours must be upper level (see Domains in Data Science and Data Analytics for further information). Additional elective hours may be required dependent on chosen domain. Sem. Hrs: 21-22

Arkansas State University

www.astate.edu

Data Science and Data Analytics, Emphasis in Data Science, BS

University Requirements:

First Year Making Connections Course:

General Education Requirements:

Students with this major must take the following:

Major Requirements (Program Core):

Sub-total: 37

Emphasis Area (Data Science):

Sub-total: 24

Domain Studies (Data Science Emphasis):

Total Required Hours: 120

www.astate.edu

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Data Science and Data Analytics, Emphasis in Data Science, BS

University Requirements:

First Year Making Connections Course:

General Education Requirements:

Students with this major must take the following:

Major Requirements (Program Core):

Sub-total: 37

Emphasis Area (Data Science):

Sub-total: 24

Domain Studies (Data Science Emphasis):

Total Required Hours: 120