Master of Science (MS) Degree Program in Computational and Applied Mathematics

Students completing the MS program will have acquired highly marketable techniques involving networks, complex systems, machine learning, and data analysis alongside more traditional topics such as probability, statistics, computational methods, and other applied mathematics methods.

The MS program includes three tracks:

• Applied Probability and Statistics Track
  
• Computation Track (including high-performance computing, data-intensive computing, and data science)
  
• Complex Systems Track (including network science)

Degree Requirements:

The MS program comprises a total of thirty-three (33) credit hours, divided among: seven (7) required courses (21 credit hours);  three (3) electives (9 credit hours), chosen based on the concentration area selected and student’s specific interests; and, a final project (3 credit hours).
 

REQUIRED COURSES
(24 credit hours including a final project MTH 589; 3 credit hours for each course):

• Applied Probability and Statistics Track
  

      Term 1: Fall 1

            MTH 511: Probability Theory

            MTH 537: Introduction to Numerical Analysis 1

            MTH 543: Fundamentals of Applied Mathematics 1

            (Elective 1)

      Term 2: Spring 1

            MTH 512: Introduction to Statistical Inference

            MTH 538: Introduction to Numerical Analysis 2

            MTH 548: Data-oriented Computing

            (Elective 2)

      Term 3: Fall 2

            MTH 546: Stochastic Processes

            MTH 589: Project Guidance

            (Elective 3)

• Computation Track

      Term 1: Fall 1

            MTH 511: Probability Theory

            MTH 537: Introduction to Numerical Analysis 1

            MTH 543: Fundamentals of Applied Mathematics 1

            (Elective 1)

      Term 2: Spring 1

            MTH 512: Introduction to Statistical Inference

            MTH 538: Introduction to Numerical Analysis 2

            MTH 548: Data-oriented Computing

            (Elective 2)

      Term 3: Fall 2

            MTH 667: High Performance Computing 1

            MTH 589: Project Guidance

            (Elective 3)

• Complex Systems Track

      Term 1: Fall 1

            MTH 511: Probability Theory

            MTH 537: Introduction to Numerical Analysis 1

            MTH 543: Fundamentals of Applied Mathematics 1

            MTH 555: Complex Systems

      Term 2: Spring 1

            MTH 512: Introduction to Statistical Inference

            MTH 538: Introduction to Numerical Analysis 2

            MTH 548: Data-oriented Computing

            (Elective 1)

      Term 3: Fall 2

            MTH 589: Project Guidance

            (Elective 2)

            (Elective 3)

• MTH 539: Methods of Applied Mathematics 1
• MTH 550: Network Theory
• MTH 555: Introduction to Complex Systems
• MTH 558: Mathematical Finance 1
• MTH 559: Mathematical Finance 2
• MTH 644: Large Deviations Theory and Rare Event Simulation
• Any graduate-level elective course approved by the program director
  
  

Computation Track

• MTH 555: Introduction to Complex Systems
  
• MTH 637: Advanced Numerical Analysis 1
• MTH 644: Large Deviation Theory and Rare Event Simulation
• MTH 648: Data-Oriented Computing 2
• CSE 574: Introduction to Machine Learning
• Any graduate-level elective course approved by the program director

Complex Systems Track

• MTH 546: Stochastic Processes (currently taught as a topics class; also MTH 563)
• MTH 550: Network Theory
• MTH 644: Large Deviations Theory and Rare Event Simulation
• MTH 648: Data-Oriented Computing 2
• Any graduate-level elective course approved by the program director

ESTIMATED TIME TO COMPLETION
The MS program can be completed in 1.5-years at twelve (12) credit hours per semester. This program only accepts students starting in the Fall Semester.