Graduate Coordinator: Seong-Tae “Ty” Kim Email: skim@ncat.edu Phone: 336-285-4758
Department Chair: Guoqing Tang Email: tang@ncat.edu Phone: 336-285-2089
The Master of Science in Data Analytics (MSDAAN) degree program at North Carolina A&T
State University - America’s largest HBCU - prepares students for careers in a field of growing
national need, with an online option designed for working professionals. The MSDAAN program
imparts advanced knowledge on current and future practices and tools to examine data sets,
conduct analysis of the data, and draw conclusions about the information they contain.
Students will be able to:
• Develop a comprehensive understanding and mastery of state-of-the-art data analytics
techniques.
• Practice data-driven problem analysis, information retrieval, and decision-making.
• Gain practical, hands-on experience with various programming languages, data analysis,
and visualization tools through coursework and project-based learning experiences.
• Identify, acquire, manage, present, analyze, and interpret large amounts of data from
various applications in health, business, education, journalism, and criminal justice.
• Predict future outcomes based on historical data.
• Identify appropriate statistical and predictive methodologies for use with both sparse and
large data sets.
• Create effective and powerful visual representations of complex data to enhance
understanding of the data and to identify data patterns.
Essential skills students will learn include:
• Statistical inference and modeling
• R, Python, Tableau and/or SQL programming
• Data extraction, processing and wrangling
• Data mining and machine learning algorithms
• Big data analytics and cloud computing
• Data
Admission Requirements
Applicants must have a B.S. degree in STEM, business and economics, behavioral and health
sciences, agricultural economics, education, or a B.A./B.S. degree in humanities or social
sciences with at least a 3.0 undergraduate GPA. Additionally, applicants must have an adequate
preparation in statistics, computer programming and problem-solving. Specifically, applicants
must have completed the following undergraduate level courses or equivalent:
• One course in probability and statistics, and
• One course in algorithmic problem-solving using a data analysis and visualization
programming language such as Python, R or MATLAB.
If an applicant fails to meet the prerequisite course requirements, the student will be required to
take one or two courses below to fulfill the prerequisite course requirements:
• STAT 214: Introduction to Statistical Reasoning, or
• MATH 224: Introduction to Probability and Statistics, or
• ECON 206: Statistics for Decision Making
• MATH 140: Fundamentals of Scientific Programming with Python, or
• CST 140: Introduction to Computer Programming, or
• COMP 161: Python for Data Science
Students must earn at least a “B” in these courses. Students with prerequisite deficiencies are
required to complete these courses before they start the program.
Up to 12 hours of graduate-level credit can be transferred from another accredited institution.
Grade earned on transfer work must be equivalent to a “B” or better. Transfer courses must be
approved by the Program Coordinator.
Return to: