Program Description

The Master of Science with a major in Data Science and Analytics Program (MSDSA) at Kennesaw State University is a 36 semester-hour applied, professional degree program which seeks to prepare a diverse student body to utilize cutting edge data science and analytics methods to enable correct, meaningful inferences from data obtained from business, industry, government, and health services. The MSDSA program is open to all individuals looking to advance their careers in data science and analytics. The MSDSA program focuses on the following areas:

1. Practical, hands-on experience with programming languages and big data tools, through coursework and applied research experiences.
2. Application of data science and analytical methods and techniques to mine and visualize data for patterns and relationships.
3. Identifying, building, and evaluating appropriate models for a variety of data science tasks.
4. Obtaining, cleaning, processing, and transforming data for analysis and modeling.
5. Effectively interpreting and communicating analysis methods and findings to any audience, orally, visually, and in written formats.

Students may take up to 9 credit hours in related disciplines (e.g. AI,  CS, IT, SWEG, IS) to help complement their data science and analytics education and learn additional computational, analytical, and programming knowledge and skills.

Program Student Learning Outcomes

Students who successfully complete this program will be able to:

1. Effectively investigate large, raw data sets using statistical software to develop previously unknown insights from various sources.
2. Apply foundational and advanced analytical methods and techniques to prepare, analyze, visualize, model, and interpret data for a variety of data science tasks and objectives.
3. Effectively interpret and communicate analysis methods and findings to any audience, orally, visually, and in written formats.

This program is a part of the College of Computing and Software Engineering .

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Admission, Enrollment, and Graduation Policies

Admission Criteria

The following are program-specific criteria beyond the general Graduate Admissions requirements:

• Resume
  • This should include any relevant professional certifications, activities, work activities, and/or completed projects.

Streamlined Application Process:

Students who meet the following qualification are eligible for a streamlined application process. To qualify students must:

• Be a current Kennesaw State University student majoring in one of the College of Computing and Software Engineering’s undergraduate programs.
• Have an active petition to graduate in that major
• Have a 3.5 GPA or higher upon graduation and the recommendation of the undergraduate coordinator
• Students who meet these criteria are not required to take the GRE nor submit secondary documentation that includes a resumé or vita.

Admission Criteria for Unique Cases

The MS in Data Science and Analytics requires students to have fundamental knowledge in calculus, statistics/probability, and computing. A student with an insufficient background may be conditionally admitted. Conditions may be fulfilled by successfully completing foundation coursework or successfully completing foundation modules offered by KSU Community and Professional Education (CPE). Upon successful completion of conditions, the student will achieve full graduate status. A student can satisfy the prerequisite conditions for the MS in Data Science and Analytics in one of the following two manners:

1. By completing up to 4 designated foundation courses with a grade of “B” or better:

• MATH 1190: Calculus I
• MATH 2202: Calculus II
• STAT 1401: Elementary Statistics
• DATA 3010: Computer Applications of Statistics

2. By completing up to 3 designated foundation modules offered through KSU CPE.

• Introduction to Mathematics for Data Science and Analytics
• Introduction to Statistical Thinking
• Essential Softwares for Data Science and Analytics

Transfer Credits

See Policy 6.1 .

Enrollment Criteria

This program does not have specific enrollment criteria; however, students are expected to meet the requirements of Academic Policy 4.0 ACADEMIC STANDING, DISMISSAL, & REINSTATEMENT .

Graduation Criteria

Each student is expected to meet the requirements outlined in Academic Policy 5.0 PROGRAM REQUIREMENTS & GRADUATION .

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Program Course Requirements