Master of Science in Data Analytics
The Master of Science in Data Analytics (MSDAAN) degree program at North Carolina A&T State University – American’s largest HBCU – prepares students for careers in a field of growing national need, with the online option designed for working professionals. The MSDAAN imparts advanced knowledge on current and future practices and tools to examine data sets, conduct an 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 statistical 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
- Data visualization and communications
The M.S. in Data Analytics program is a collaboration among the colleges of Science and Technology (CoST), Arts, Humanities and Social Sciences (CAHSS), Business and Economics (COBE), Education (CoED) and Health and Human Sciences (CHHS) at N.C. A&T. It particularly builds upon the strengths of two departments in the College of Science and Technology: the Department of Mathematics and Statistics and the Department of Computer Systems Technology. Students will benefit from a truly interdisciplinary program.
Why Get an M.S. in Data Analytics Degree?
Our world is increasingly data-driven, with the production of digital information growing rapidly each year. According to a 2020 report from Seagate and independent research firm IDC, the amount of data generated is expected to reach 175 zettabytes – that’s a trillion gigabytes – by 2025. As a result, there is a tremendous need for workers skilled in handling and analyzing this data in all industries, as businesses and governments rely on data analysis to make important, high-stakes decisions. Big data analysis was one of the highest company priorities in the World Economic Forum’s 2020 Future of Jobs Survey. Among jobs showing increasing demand, data analysts and scientists was No. 1 and big data specialists was No. 3 in the same survey.
Students in this program will become effective predictive modelers, engaging team players and persuasive communicators. Graduates will also be up-to-date on the latest technologies, have greater earning potential and be more competitive in the job market. In a 2021 Burtch Works survey, well over half of data scientists surveyed had an advanced degree.
Program Snapshot
- Credits required: 30
- Time to completion: 2 years if full-time
- Tuition: Distance Learning Tuition and Fees
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Potential Careers
Graduates of the program will improve and enhance their employers’ business operations by providing insights and support in data-driven decision-making. High-paying data analytics jobs include:
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Job Outlook
The Bureau of Labor Statistics projects employment of data scientists to grow 36% nationally from 2021 to 2031, one of their Top 10 fastest-growing occupations, with 40,500 jobs added. An additional 24,200 operations research analyst jobs are projected over the same period, an increase of 23%. Both are projected to grow much faster than average.
Salary
Median pay, data scientists (May 2021): $100,910 per year (BLS.gov)
Median pay, operations research analysts (May 2021): $82,360 per year (BLS.gov)
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.
Find out more about graduate admissions and APPLY TODAY.
Application Deadlines
| Fall admission | Spring admission | |
| Priority | Jan. 15 | |
| General | July 1 | Nov. 1 |
Program Requirements
The Master of Science in Data Analytics requires 30 credit hours with a choice of one of five concentrations:
- Health Analytics
- Education Analytics
- Social and Human Analytics
- Business Analytics
- Advanced Analytics
Students have a maximum of five years from initial enrollment to complete the program. To maintain good academic standing, students must maintain a minimum cumulative GPA of 3.0. The curriculum is comprised of:
Five core courses (15 credit hours)
- STAT 707: Introduction to Data Science & Analytics
- DAAN 703: Data Wrangling and Visualization
- STAT 709: Statistical Foundations of Data Analytics
- DAAN 704: Predictive Analytics and Machine Learning
- DAAN 705: Data Privacy, Ethics and Security
One required course and three elective courses from the selected concentration (12 credit hours). The required concentration courses are:
- Health Analytics: DAAN 706, Fundamentals of Health Analytics
- Education Analytics: DAAN 707, Fundamentals of Education Analytics
- Social and Humanities Analytics: DAAN 708, Fundamentals of Social and Humanities Analytics
- Business Analytics: STAT 823, Time Series and Business Analytics
- Advanced Analytics: STAT 710, Statistical Deep Learning
Master’s Practicum in Data Analytics (3 credit hours)
Funding Your Education
North Carolina A&T has established a number of financial support opportunities for outstanding graduate students in order to enhance research and graduate education. These include fellowships, scholarships, assistantships and out-of-state tuition supplements.
Contact Information
For program-related questions:
Seong-Tae “Ty” Kim, Ph.D.
Program Coordinator
Department of Mathematics and Statistics
College of Science and Technology
Email
336-285-4758
or
Guoqing Tang, Ph.D.
Chair, Department of Mathematics and Statistics
College of Science and Technology
Email
336-285-2089
For assistance with the admissions process:
The Graduate College
Email
336-285-2366
For online learning support and inquiries:
Extended Campus
Email
336-334-7810 or 888-498-6752 (Toll-Free)