College of Science and Technology

Master of Science Degrees in Applied Mathematics and Data Analytics

The M.S. Degree Programs in Applied Mathematics and Data Analytics at North Carolina A&T provide an educational program in which the student is given a thorough background and research training in one of the key areas of Applied Mathematics and Data Analytics, as well offering the students hands-­on experience in current important applications in applied mathematics areas, along with the statistical and computational skills to apply their knowledge to tackle real world applications.

 

Graduate Financial Support

  • Graduate teaching assistantships, research assistantships and fellowships are available. Please contact the Department Chair for details of the graduate support.

 

Master of Science in Applied Mathematics

Admission Requirements

A student seeking the Master of Science in Applied Mathematics must complete the following:

  • 30 credit hours of graduate course work.
  • Three core courses (9 credit hours): MATH 603, 651, and 690.
  • A thesis, a project, or specialized coursework.

 

Thesis option:

  • Take 9 credit hours of core courses
  • Take 9 credit hours of 700 or 800 level MATH or STAT courses with approval of advisor
  • Take 6 credit hours of additional graduate courses with approval of advisor
  • Master’s Thesis (MATH 797: 6 credit hours)
  • Pass Master’s Thesis defense

 

Project Option:

  • Take 9 credit hours of core courses
  • Take 12 credit hours of graduate MATH or STAT courses with at least 9 hours of coursework at 700 level or above and approval of advisor
  • Take 6 credit hours of additional graduate courses with approval of advisor
  • Graduate Design Project (MATH 796: 3 credit hours)
  • Pass Graduate Design Project oral examination

 

Coursework Option:

  • Take 9 credit hours of core courses
  • Take 12 credit hours of graduate MATH or STAT courses with at least 9 hours of coursework at 700 level or above and approval of advisor
  • Take 6 credit hours of additional graduate courses with approval of advisor
  • Take 2 credit hours of MATH 784- Master’s Practicum and 1 credit hour of MATH 705- Graduate Seminar, OR

Take 1 credit hour of MATH 705- Graduate Seminar three times

 

 


 

Core courses (9 credit hours):

MATH 603- Introduction to Real Analysis (3)

MATH 651- Partial Differential Equations (3)

MATH 690- Scientific Programming for Mathematical Scientists (3)

 

Electives:

MATH 610- Complex Variables (3)

MATH 612-Advanced Linear Algebra (3)

MATH 631- Linear and Non-Linear Programming (3)

MATH 633- Stochastic Processes (3)

MATH 650- Ordinary Differential Equations (3)

MATH 652- Methods of Applied Mathematics (3)

MATH 665- Principles of Optimization (3)

MATH 675- Graph Theory (3)

MATH 685- Special Topics in Applied Mathematics (3)

MATH 700- Theory of Functions of One Real Variable I (3)

MATH 701- Theory of Functions of One Real Variable II (3)

MATH 705- Graduate Seminar (3)

MATH 709- Discrete and Combinatorial Mathematics for Data Science (3)

MATH 710- Theory of Functions of One Complex Variable (3)

MATH 712-Numerical Linear Algebra (3)

MATH 717- Special Topics in Algebra (3)

MATH 720- Special Topics in Analysis (3)

MATH 723- Advanced Topics in Applied Mathematics (3)

MATH 731- Advanced Numerical Methods (3)

MATH 733- Advanced Probability & Stochastic Process (3)

MATH 752- Calculus Variations and Control Theory (3)

MATH 761- Interdisciplinary Computational Science Project I (3)

MATH 762- Interdisciplinary Computational Science Project II (3)

MATH 781- Mathematical & Computational Modeling (3)

MATH 782- Statistical Data Analytics and Visualization (3)

MATH 784- Master’s Practicum (2)

MATH 796- Graduate Design Project (3)

MATH 797- Thesis Research in Mathematics (3)

MATH 799- Continuation of Thesis for Mathematics (1)

MATH 885- Special Topics in Data Science and Analytics (3)

STAT 703- Probability Theory and Applications (3)

STAT 704- Statistical Inference (3)

STAT 707- Introduction to data Science (3)

STAT 708- Linear Models for Data Science (3)

STAT 709-Statistical Foundations of Machine Learning (3)

STAT 710- Statistical and Deep Learning (3)

STAT 711- Statistical Computing and Algorithm Analysis (3)

STAT 713- Sample Survey Methods (3)

STAT 723- Categorical Data Analysis (3)

STAT 727- Multivariate Statistical Analysis (3)

STAT 808- Advanced Regression Methods for Data Science (3)

A student seeking the Master of Science in Applied Mathematics with a Concentration in Statistics and Data Sciencemust complete the following:

  • 30 credit hours of graduate course work.
  • Three core courses (9 credit hours): MATH 603 or STAT 703, MATH 650 or MATH 651 or STAT 704, and MATH 690 or STAT 707.
  • A thesis, or a project, or specialized coursework

 

Thesis option:

  • Take 9 credit hours of core courses
  • Take 9 credit hours of 700 or 800 level STAT or MATH courses with approval of advisor
  • Take 6 credit hours of additional graduate courses with approval of advisor
  • Master’s Thesis (MATH 797-Master’s Thesis: 6 credit hours)
  • Pass Master’s Thesis defense

 

Project Option:

  • Take 9 credit hours of core courses
  • Take 12 credit hours of graduate STAT or MATH courses with at least 9 hours of coursework at 700 level or above, and approval of advisor
  • Take 6 credit hours of additional graduate courses with approval of advisor
  • Graduate Design Project (MATH 796-Graduate Design Project: 3 credit hours)
  • Pass Graduate Design Project oral examination

 

Coursework Option:

  • Take 9 credit hours of core courses
  • Take 12 credit hours of graduate STAT or MATH courses with at least 9 hours of coursework at 700 level or above, and approval of advisor
  • Take 6 credit hours of additional graduate courses with approval of advisor
  • Take 2 credit hours of MATH 784- Master’s Practicum and 1 credit hour of MATH 705-Graduate Seminar, OR

Take 1 credit hour of STAT 777-Statistical Consulting Practice twice and 1 credit hour of MATH 705-Graduate Seminar

 

 

Core courses (9 credit hours):

COURSE 1:

MATH 603-Introduction to Real Analysis (3) OR

STAT 703- Probability Theory and Applications (3)

 

COURSE 2:

MATH 650- Ordinary Differential Equations (3) OR

MATH 651- Partial Differential Equations (3) OR

STAT 704- Statistical Inference (3)

 

COURSE 3:

MATH 690- Scientific Programming for Mathematical Scientists (3) OR

STAT 707- Introduction to Data Science (3)

 

Electives:

MATH 612- Advanced Linear Algebra (3)

MATH 633- Stochastic Processes (3)

MATH 665- Principles of Optimization (3)

MATH 705- Graduate Seminar (3)

MATH 705- Graduate Seminar (3)

MATH 709- Discrete and Combinatorial Mathematics for Data Science (3)

MATH 712- Numerical Linear Algebra (3)

MATH 731- Advanced Numerical Methods (3)

MATH 733- Advanced Probability & Stochastic Process (3)

MATH 781- Mathematical & Computational Modeling (3)

MATH 782- Statistical Data Analytics and Visualization (3)

MATH 784- Master’s Practicum (2)

MATH 796- Graduate Design Project (3)

MATH 797- Thesis Research in Mathematics (3)

MATH 799- Continuation of Thesis for Mathematics (1)

MATH 885- Special Topics in Data Science and Analytics (3)

STAT 708- Linear Models for Data Science (3)

STAT 709- Statistical Foundations of Machine Learning (3)

STAT 710- Statistical and Deep Learning (3)

STAT 711- Statistical Computing and Algorithm Analysis (3)

STAT 712- Bayesian Statistics (3)

STAT 713- Sample Survey Methods (3)

STAT 722- Nonparametric Statistics (3)

STAT 723- Categorical Data Analysis (3)

STAT 727- Multivariate Statistical Analysis (3)

STAT 777- Statistical Consulting Practice (1)

STAT 808- Advanced Regression Methods for Data Science (3)

STAT 810- Causal Inference and Learning (3)

STAT 823- Time Series and Business Analytics (3)

STAT 824- Biostatistics and Health Analytics (3)

COMP 620- Data Analytics Techniques (3)

COMP 851- Big Data Analytics (3)

COMP 852- Web-Based Visual Analytics (3)

COMP 853- Data Fusion (3)

 

 

 

A student seeking the Master of Science in Applied Mathematics with a Concentration in Mathematics Education Research and Assessment must complete the following:

  • 30 credit hours of graduate course work.
  • Three core courses (9 credit hours): MATH 602 or MATH 603 or MATH 612, MATH 651 or MATH 650 or MATH 612, and MATH 601 or MATH 690 or STAT 707.
  • A thesis, or a project, or specialized coursework

 

Thesis option:

  • Take 9 credit hours of core courses
  • Take 9 credit hours of 700 or 800 level MATH or STAT courses with approval of advisor
  • Take 6 credit hours of graduate education courses with approval of advisor
  • Master’s Thesis (MATH 797-Master’s Thesis: 6 credit hours)
  • Pass Master’s Thesis defense

 

Project Option:

  • Take 9 credit hours of core courses
  • Take 12 credit hours of graduate MATH or STAT courses with at least 9 hours of coursework at 700 level or above and approval of advisor
  • Take 6 credit hours of graduate education courses with approval of advisor
  • Graduate Design Project (MATH 796-Graduate Design Project: 3 credit hours)
  • Pass Graduate Design Project oral examination

 

Coursework Option:

  • Take 9 credit hours of core courses
  • Take 12 credit hours of graduate MATH or STAT courses with at least 9 hours of coursework at 700 level or above and approval of advisor
  • Take 6 credit hours of graduate education courses with approval of advisor
  • Take 2 credit hours of MATH 784-Master’s Practicum and 1 credit hour of MATH 705-Graduate Seminar, OR

Take 1 credit hour of MATH 705-Graduate Seminar three times

 

 

 

Core courses (9 credit hours):

COURSE 1:

MATH 602-Modern Algebra (3) OR

MATH 603-Introduction to Real Analysis (3) OR

MATH 612- Advanced Linear Algebra (3)

 

COURSE 2:

MATH 650- Ordinary Differential Equations (3) OR

MATH 651- Partial Differential Equations (3) OR

STAT 705- Applied Statistics for Biological and Behavioral Sciences (3)

 

COURSE 3:

MATH 601- Technology and Applications in Secondary School Mathematics (3) OR

MATH 690- Scientific Programming for Mathematical Scientists (3) OR

STAT 707- Introduction to Data Science

 

Electives:

MATH 604- Modern Geometry for Secondary School Teachers (3)

MATH 610- Complex Variables (3)

MATH 631- Linear and Non-Linear Programming (3)

MATH 665- Principles of Optimization (3)

MATH 675- Graph Theory (3)

MATH 685- Special Topics in Applied Mathematics (3)

MATH 705- Graduate Seminar (3)

MATH 709- Discrete and Combinatorial Mathematics for Data Science (3)

MATH 710- Theory of Functions of One Complex Variable (3)

MATH 712-Numerical Linear Algebra (3)

MATH 723-Advanced Topics in Applied Mathematics (3)

MATH 731- Advanced Numerical Methods (3)

MATH 765- Optimization Theory and Applications (3)

MATH 781- Mathematical & Computational Modeling (3)

MATH 782- Statistical Data Analytics and Visualization (3)

MATH 784- Master’s Practicum (2)

MATH 796- Graduate Design Project (3)

MATH 797- Thesis Research in Mathematics (3)

MATH 799- Continuation of Thesis for Mathematics (1)

STAT 703- Probability Theory and Applications (3)

STAT 704- Statistical Inference (3)

STAT 707- Introduction to Data Science (3)

STAT 708- Linear Models for Data Science (3)

STAT 709- Statistical Foundations of Machine Learning (3)

STAT 713- Sample Survey Methods (3)

STAT 716- Design and Analysis of Educational Experiments (3)

STAT 723- Categorical Data Analysis (3)

STAT 727- Multivariate Statistical Analysis (3)

STAT 808- Advanced Regression Methods for Data Science (3)

EDPR 611-Instructional Planning (3)

EDPR 612-Planning and Assessing Literacy (3)

EDPR 615-Assessment of Learning (3)

EDPR 620-Advanced Pedagogical Strategies (3)

 

Master of Science in Data Analytics

  • A Bachelor’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.
  • Complete online application at https://aggieadmissions.ncat.edu/graduateadmissions/default.asp

Degree Requirements

Total credit hours: 30

  • Core courses (15 credit hours): DAAN 703, DAAN 704, DAAN 705, STAT 707, and STAT 709
  • Two concentrations: Advanced Analytics, and Business Analytics

Coursework Option:

  • Take 15 credit hours of core courses
  • Take 12 credit hours of one required course and three elective courses from the selected concentration
    • The requirement of each concentration
      • Advanced analytics: STAT 710 Statistical Deep Learning
      • Business analytics: STAT 823 Time Series Bus Analytics
    • The list of elective courses is given below.
  • Take 3 credit hours of Master’s Practicum in Data Analytics (DAAN 784)

 

Suggested Electives for Advanced Analytics (12 hours)

  • STAT 708: Linear Models for Data Science
  • STAT 710: Statistical Deep Learning
  • STAT 711: Stat Comp and Algorithm Analy
  • STAT 712: Bayesian Statistics
  • STAT 722: Nonparametric Statistics
  • STAT 723: Categorical Data Analysis
  • STAT 727: Multivariate Statistical Analy
  • STAT 808: Adv Regression Meth Data Sci
  • STAT 810: Causal Inference & Learning
  • STAT 823: Time Series Bus Analytics
  • CST 764: Advanced Big Data Analytics
  • MATH 885: Sp Tpcs Data Sci/Analyt

 

Degree Requirements

Total credit hours: 30

  • Core courses (15 credit hours): DAAN 703, DAAN 704, DAAN 705, STAT 707, and STAT 709
  • Two concentrations: Advanced Analytics, and Business Analytics

Coursework Option:

  • Take 15 credit hours of core courses
  • Take 12 credit hours of one required course and three elective courses from the selected concentration
    • The requirement of each concentration
      • Advanced analytics: STAT 710 Statistical Deep Learning
      • Business analytics: STAT 823 Time Series Bus Analytics
    • The list of elective courses is given below.
  • Take 3 credit hours of Master’s Practicum in Data Analytics (DAAN 784)

Suggested Electives for Business Analytics (12 hours)

  • BUAN 725: Business Analytics
  • BUAN 740: Data Analys & Busi Intel Appli
  • BUAN 605: Methods in Business Analysis
  • MIS 744: Enterprise Data Management
  • CST 625: Computer Database Management
  • CST 729: Data Warehousing
  • CST 731: Knowledge Discovery Systems
  • STAT 823: Time Series Bus Analytics

 
Contact Information

Dr. Alexandra Kurepa
Graduate Coordinator
Department of Mathematics
North Carolina A&T State University
Greensboro, NC 27411
Office: 111 Marteena Hall
Phone: 336-285-2079 
E-mail: kurepa@ncat.edu

Or

Dr. Guoqing Tang, Chair
Department of Mathematics
102 Marteena Hall
Phone: 336-285-2089 
E-mail: tang@ncat.edu

 

Faculty Areas of Specialization

  • Differential Equations
  • Numerical Analysis
  • Biomathematics
  • Biostatistics
  • Nonlinear & Dynamic Programming
  • Mathematical Control & Optimization
  • Stochastic Modeling
  • Mathematical Economics and Finance
  • Mathematical Geosciences
  • Nonlinear Waves and Optics
  • Data Science & Analytics
  • Big Data Analysis & Presentation
  • Information Security
  • Machine Learning
  • Time Series Analysis
  • Health Informatics
  • Signal and Image Processing