Bachelor of Science in Data Science and Analytics

The School of Data Science and Analytics is pleased to announce that the Board of Regents of the University System of Georgia at their April 19th, 2023 meeting approved Kennesaw State University to begin offering a Bachelor of Science in Data Science and Analytics beginning in Fall 2023. We are both grateful to the Regents and excited to launch this next phase of our School!

Catalog Listing

If you are interested in the program or have questions about it, please feel free to reach out to any of the following people:

Michael Frankel, mfranke1@kennesaw.edu
Senior Lecturer and Coordinator of the Minor in Data Science and Analytics

Sherrill Hayes, shayes32@kennesaw.edu
Director of the School of Data Science and Analytics

Leann Levelsmier, lhaman1@kennesaw.edu
Office Manager, School of Data Science and Analytics

Cara Reeve cmisurac@kennesaw.edu
Program Coordinator, School of Data Science and Analytics

About BSDSA Program

The Bachelor of Science with a major in Data Science and Analytics will provide a student with foundational mathematical, statistical, and computational knowledge, skills, and methodologies within the context of the ethical and professional standards of Data Science. A student will also complete at least 16 hours of courses in either a domain of expertise in data science and analytics or a minor to provide them a context in which to apply their data science abilities. Thus, the degree will enable the student to either begin a career in industry, government, or community and non-profit organizations in a range of domains, or pursue graduate study.

Students will begin the program by building a foundation in mathematics, statistics, computer programming, and algorithmic techniques. They will then take 38 credit hours of data science core courses covering the fundamentals of data science, programming, machine learning, data mining, data science ethics, and communication. After completing the core, students will complete 6 credit hours of elective courses in data science and statistical learning. Students will also be required to take at least 16 hours in a suitable domain knowledge concentration to begin exploring an expert area of application. The program will conclude with a required data science capstone course, in which the student will demonstrate overall knowledge of the discipline by completing a data science project, incorporating all the knowledge learned in the courses.

Curriculum

General Education Core Curriculum (Areas A-E) (42 Credit Hours)

General Education Core Curriculum

General Education Core Curriculum Requirements Specific to this Major

Science Majors must take MATH 1113 or higher in Area A2 and MATH 1190 or higher in Area D1.

Science and Engineering Majors must take two four-hour laboratory sciences in Area D2.
Students must choose from CHEM 1211/L, CHEM 1212/L, PHYS 1111/L*, PHYS 1112/L*, PHYS 2211/L*, PHYS 2212/L*, BIOL 1107/L, or BIOL 1108/L.
* Students cannot take both PHYS 1111/L and PHYS 2211/L nor PHYS 1112/L and PHYS 2212/L.

Lower Division Major Requirements (Area F) (18 Credit Hours)

MATH 2202 - Calculus II
CSE 2300 - Discrete Structures for Computing
or
MATH 2345 - Discrete Mathematics
STAT 1401 - Elementary Statistics
or
STAT 2332 - Probability and Data Analysis
CSE 1321 - Programming and Problem Solving I
CSE 1321L - Programming and Problem Solving I Laboratory
CSE 1322 - Programming and Problem Solving II
CSE 1322L - Programming and Problem Solving II Laboratory

Major Requirements (38 Credit Hours)

One carry over credit hour from Area D1
One carry over credit hour from Area D2
DATA 3010 - Computer Applications of Statistics
STAT 3120 - Statistical Methods I
or
STAT 3125 - Biostatistics
STAT 3130 - Statistical Methods II
DATA 3230 - Data Visualization
MATH 3260 - Linear Algebra I
DATA 3300 - Data Science Ethics
CSE 3153 - Database Systems
or
CS 3410 - Introduction to Database Systems
DATA 4000 - Data Science Communication
DATA 4030 - Programming in R
or
DATA 4140 - Python for Data Science
STAT 4210 - Applied Regression Analysis
DATA 4310 - Statistical Data Mining
DATA 4990 - Data Science Capstone

Major Electives (6 Credit Hours)

Select six credit hours from the following:

DATA 3396 - Cooperative Study
DATA 3398 - Internship
STAT 4025 - Clinical Trial Design
DATA 4030 - Programming in R
STAT 4120 - Applied Experimental Design
STAT 4125 - Analysis of Human Studies
DATA 4330 - Applied Binary Classification
DATA 4400 - Directed Study
DATA 4490 - Special Topics in Statistics
DATA 4140 - Python for Data Science
CSE 4983 - CSE Computing Internship

Related Studies (16 Credit Hours)

A minimum of sixteen hours of additional courses taken at the 1000-4000 level. Students are encouraged to take courses that focus on a particular domain with data science applications. These hours can also be used to earn a minor in another discipline.