Three elective courses must be taken from the following list. Course substitutions are encouraged (with advisor approval). Students are suggested to include electives that strengthen computing skills, such as SAS, SQL, VBA, C, C++, and Java.

CSC 505 Design and Analysis Of Algorithms
CSC 522 Automated Learning and Data Analysis
CSC 540 Database Management Concepts and Systems
CSC 541 Advanced Data Structures
CSC/MA 580 Numerical Analysis I
CSC/MA 583 Introduction to Parallel Computing
CSC 591 Data Driven Business Intelligence (course must have this title)
CSC 591 Graph Data Mining (course must have this title)
CSC 591 Spatial and Temporal Data Mining (course must have this title)

ECG 701 Microeconomics I
ECG 702 Microeconomics II
ECG/ST 750 Introduction to Econometric Methods
ECG/ST 751 Econometric Methods
ECG/ST 752 Time Series Econometrics
ECG/ST 753 Microeconometrics

FIM/MA 549 Financial Risk Analysis

ISE 519 Database Applications in Industrial and Systems Engineering
ISE 712 Bayesian Decision Analysis For Engineers and Managers

(at most two MBA classes can be taken as an MFM elective)
MBA 515 Enterprise Systems
MBA 518 Enterprise Risk Management
MBA 521 Advanced Corporate Finance
MBA 524 Equity Valuation
MBA 526 International Finance
MBA 529 New Firm Financing

MA 515 Analysis I
MA 520 Linear Algebra
MA 523 Linear Transformations and Matrix Theory
MA 532 Ordinary Differential Equations I
MA 534 Introduction To Partial Differential Equations
MA 540 Uncertainty Quantification for Physical and Biological Models
MA 544 Computer Experiments In Mathematical Probability
MA/ST 546 Probability and Stochastic Processes I (if not taken as a Core class)
MA 555 Introduction to Manifold Theory
MA/BMA 573 Mathematical Modeling of Physical and Biological Processes I
MA/BMA 574 Mathematical Modeling of Physical and Biological Processes II
MA 584 Numerical Solution of Partial Differential Equations–Finite Difference Methods
MA 587 Numerical Solution of Partial Differential Equations–Finite Element Method
MA 715 Analysis II
MA 723 Theory of Matrices and Applications
MA/ST 746 Introduction To Stochastic Processes
MA/ST 747 Probability and Stochastic Processes II
MA/ST 748 Stochastic Differential Equations

OR/ISE 501 Introduction to Operations Research
OR/MA 504 Introduction to Mathematical Programming
OR/ISE/MA 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR/E/MA 531 Dynamic Systems and Multivariable Control I
OR/MA 719 Vector Space Methods in System Optimization
OR/ISE 772 Stochastic Simulation Design and Analysis
OR/BMA/MA/ST 773 Stochastic Modeling

ST 503 Fundamentals of Linear Models and Regression
ST 505 Applied Nonparametric Statistics
ST 512 Experimental Statistics For Biological Sciences II
ST 552 Linear Models and Variance Components
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 563 Introduction to Statistical Learning (available soon)
ST 564 Statistical Thinking and Big Data (available soon)

Students studying towards a PhD —

These courses are approved as electives, but should be considered only if studying towards a PhD; ST 708, ST 711, ST 730, ST 731, ST 732, ST 733, ST 744, ST 745, ST 758, ST 782, and ST 783.

Courses not on the pre-approved list —

If a course does not appear on this list, seek approval from your academic adviser.

You can also take classes at UNC or Duke.

Revised: 7/5/2016