Master of Science Degrees in Applied Mathematics and Data Analytics
The M.S. Degree Programs in Applied Mathematics and Data Analytics at 杏吧原创 杏吧原创 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
- Bachelor’s degree in mathematics, science, engineering, or a related field.
- Have taken Calculus I and II, Differential Equations and Linear Algebra and an upper division math course
- Complete online application at
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
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.
- The requirement of each concentration
- 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.
- The requirement of each concentration
- 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 - M.S. Applied Mathematics
E-mail: kurepa@ncat.edu
Dr. Seong-Tae “Ty” Kim
Graduate Coordinator - M.S. Data Analytics
E-mail: skim@ncat.edu
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