Study Plan Templates for Master of Science programs in Mathematics

1. Data Science: conditional admit, on campus

2. Data Science: regular admit, on campus

3. Data Science: traditional coursework, online

4. Data Science: advanced coursework, online

5. Applied Mathematics

6. Mathematics

7. Actuarial Mathematics and Quantitative Risk

Each MS program consists of 10 courses and can be completed in three semesters.


1. MS program in Data Science

5 core courses and 5 electives

Conditional admit, on campus

Term 1 (Fall)

  • MA 540 Introduction to Probability (condition for admission, counts as an elective)
  • MA 570 Analysis Review (condition for admission, counts as an elective)
  • MA 573 Linear Algebra Review (condition for admission, counts as an elective)
  • MA 541 Statistical Methods (core course)
  • Optional 5th course: 
    • MA 630 Advanced Optimization Methods (core course)
    • Elective

Term 2 (Spring)

  • MA 661 Dynamic Programming and Reinforcement Learning  (core course)
  • CS 583 Deep Learning (core course)
  • CPE 695 Applied Machine Learning (core course)
  • Optional 4th course: Elective

Term 3 (Fall)

  • MA 630 Advanced Optimization Methods (core course)
  • Elective 
  • Elective
  • Optional 4th course: Elective

2. MS program in Data Science

5 core courses and 5 electives

Regular admit, on campus

Term 1 (Fall)

  • MA 541 Statistical Methods (core course)
  • MA 630 Advanced Optimization Methods (core course)
  • CS 583 Deep Learning (core course)
  • Optional 4th course: 
    •  CPE 695 Applied Machine Learning (core course)
    • Elective

Term 2 (Spring)

  • MA 661 Dynamic Programming and Reinforcement Learning  (core course)
  • CPE 695 Applied Machine Learning (core course)
  • Elective
  • Optional 4th course: Elective

Term 3 (Fall)

  • Elective
  • Elective 
  • Elective
  • Optional 4th course: Elective

3. MS program in Data Science

5 core courses and 5 electives

Traditional coursework, online

Term 1

  • MA 570 Analysis Review
  • MA 573 Linear Algebra Review
  • MA 540 Probability

Term 2

  • MA 541 Statistical Methods
  • MA 544 Numerical Linear Algebra for Big Data

Term 3

  • MA 630 Advanced Optimization Methods
  • CPE 695 Applied Machine Learning

Term 4

  • CS 583 Deep Learning
  • MA 661 Dynamic Programming and Reinforcement Learning 

Term 5

  • CS 584 Natural Language Processing
  • * MA 641 Time Series Analysis
  • *CS 549 Distributed Systems & Cloud Computing
  • *CS 561 Database Management Systems I

*Student chooses 1 of the 3 for their 10th course.


4. MS program in Data Science

5 core courses and 5 electives

Advanced coursework, online

Term 1

  • MA 541 Statistical Methods
  • MA 544 Numerical Linear Algebra for Big Data

Term 2

  • MA 630 Advanced Optimization Methods
  • CPE 695 Applied Machine Learning

Term 3

  • CS 583 Deep Learning
  • MA 661 Dynamic Programming and Reinforcement Learning

Term 4

  • CS 584 Natural Language Processing
  • MA 641 Time Series Analysis

TERM 5

  • CS 549 Distributed Systems & Cloud Computing  
  • CS 561 Database Management Systems I

5. MS program in Applied Mathematics

7 core courses (3 common core course and 4 specific for each concentration) and 3 electives

Term 1 (Fall)

  • MA 635 Functional Analysis I
  • MA 540 Introduction to Probability or MA 611 Probability
  • MA 615 Numerical Analysis
  • Optional 4th course:  
    • MA 541 Statistical Methods or MA 629 Nonlinear Optimization (core courses for concentration in Optimization of Stochastic Systems)
    • MA 541 Statistical Methods (core course for concentration in Data Science)
    • MA 650 Partial Differential Equations (core course for concentration in Differential Equations)

Term 2 (Spring)

For concentration in Optimization of Stochastic Systems

  • MA 612 Mathematical Statistics (core course in place of MA 541 Statistical Method)
  • MA 623 Stochastic Processes
  • MA 662 Stochastic Optimization (core course)
  • Optional 4th course: elective

For concentration in Data Science

  • MA 544 Numerical Linear Algebra for Big Data  (core course)
  • MA 612 Mathematical Statistics (core course in place of MA 541 Statistical Method)
  • MA 641 Time Series Analysis I (core course)
  • MA 661 Dynamic Programming and Reinforcement Learning (core course)

For concentration in Differential Equations

  • MA 649 Intermediate Differential Equations (core course)
  • MA 653 Numerical Solutions of Partial Differential Equations (core course)
  • MA 681 Complex Analysis (core course)
  • Optional 4th course: Elective 

Term 3 (Fall)

  • MA 629 Nonlinear Optimization (core course for concentration in Optimization of Stochastic Systems if not taken in Term 1 (Fall))
  • MA 541 Statistical Methods (core course for concentration in Data Science if neither MA 541 nor MA 612 were taken in Term 1 (Fall) and Term 2 (Spring))
  • MA 650 Partial Differential Equations (core course for concentration in Differential Equations if not taken in Term 1 (Fall))
  • Elective
  • Elective 
  • Optional 4th course: Elective 

6. MS program in Mathematics

7 core courses (3 common core course and 4 specific for each concentration) and 3 electives

Term 1 (Fall)

  • MA 605 Foundations of Algebra I (core course) 
  • MA 611 Probability (core course) 
  • MA 635 Functional Analysis I (core course) 
  • Optional 4th course: 
  • MA 620 Introduction to Network and Graph Theory (core course for concentration in pure mathematics)
  • MA 503 Discrete Mathematics for Cryptography or MA 620 Introduction to Network and Graph Theory (core course for concentration in discrete mathematics and computation)
  • MA 503 Discrete Mathematics for Cryptography (core course for concentration in mathematical cryptography and quantum algorithms)

Term 2 (Spring) 

For concentration in pure mathematics

  • MA 606 Foundations of Algebra II (core course)
  • MA 636 Functional Analysis II  (core course)
  • MA 681 Functions of a Complex Variable I  (core course)
  • Optional 4th course:
    • MA 552 Axiomatic Linear Algebra
    • MA 649 Intermediate Differential Equations
    • MA 651 Topology I (core course)

For concentration in discrete mathematics and computation

  • MA 526 Foundations of Computation and Computational Complexity (core course, CS 601 is acceptable in place of MA 526)
  • MA 627 Combinatorial Analysis (core course)
  • MA 503 Discrete Mathematics for Cryptography or MA 620 Introduction to Network and Graph Theory (core course, if not taken in Term 1 (Fall))
  • Optional 4th course:
    • MA 503 Discrete Mathematics for Cryptography
    • MA 620 Introduction to Network and Graph Theory (core course, if not taken in Term 1 (Fall)
    • Elective

For concentration in mathematical cryptography and quantum algorithms

  • MA 526 Foundations of Computation and Computational Complexity (core course, CS 601 is acceptable in place of MA 526)
  • MA 564 Mathematics of Post-Quantum Cryptography (core course)
  • MA 503 Discrete Mathematics for Cryptography (core course, if not taken in Term 1 (Fall)) or elective
  • Optional 4th course: Elective

Term 3 (Fall)

  • MA 620 Introduction to Network and Graph Theory (core course for concentration in pure mathematics, if not taken in Term 1 (Fall))
  • MA 503 Discrete Mathematics for Cryptography or MA 620 Introduction to Network and Graph Theory (core course for concentration in discrete mathematics and computation, if not taken previously)
  • MA 565 Quantum Algorithms (core course, for concentration in mathematical cryptography and quantum algorithms)
  • Elective 
  • Elective
  • Optional 4th course: Elective

7. MS program in Actuarial Mathematics and Quantitative Risk

6 core courses and 4 electives

Term 1 (Fall)

  • MA 540 Introduction to Probability or MA 611 Probability (core course) 
  • MA 542 Actuarial Finance I (core course)   
  • Elective
  • Optional 4th course: Elective

Term 2 (Spring)

  • MA 541 Statistical Methods (core course)  
  • MA 545 Short Term Actuarial Mathematics (core course)   
  • MA 543 Actuarial Finance II (core course)   
  • Elective
  • Optional 4th course: Elective

Term 3 (Fall)

  • MA 546 Long Term Actuarial Mathematics (core course)   
  • Elective
  • Elective 
  • Optional 4th course: Elective