Approved and Denied Elective Courses

Approved Elective Courses (only approved graded electives will count)

  • AMATH 515 - Optimization: Fundamentals and Applications
  • AMATH 516- Numerical Optimization
  • AMATH 523 - Mathematical Analysis in Biology and Medicine
  • AMATH 562 - Advanced Stochastic Processes
  • BIOST 517 - Applied Biostatistics I
  • BIOST 518- Applied Biostatistics II
  • BIOST 537-Survival Data Analysis in Epidemiology
  • BIOST 544- Introduction to Biomedical Data Science (STAT MS students can take BIOST 544 if they will benefit from the computing aspect.  If they are already strong in computing, they should not take the course)
  • BIOST 550 - Statistical Genetics I: Mendelian Traits
  • BIOST 551 - Statistical Genetics II: Quantitative Traits
  • BIOST 552- Statistical Genetics III: Design and Analysis
  • BIOST 555-Statistical Methods for Spatial Epidemiology
  • BIOST 578 - (Spring 2024 only) - Special Topic: Causal Inference in Biomedical Studies
  • CFRM 505-Monte Carlo Methods in Finance
  • CFRM 506-Financial Data Access and Analysis with SQL, VBA and Excel
  • CSE 414-Introductions to Database Systems
  • CSE 417-Algorithms and Computational Complexity
  • CSE 422 Advanced Toolkit for Modern Algorithms
  • CSE 442-Data Visualization
  • CSE 447-Natural Language Processing
  • CSE 473-Introduction to Artificial Intelligence
  • CSE 493G1 (SPR 2023)-Deep Learning
  • CSE 510 - Advanced Topics in HCI
  • CSE 512 - Data Visualization
  • CSE 517-Natural Language Processing
  • CSE 535-Theory of Optimization and Continuous Algorithms
  • CSE 541 - Interactive Learning
  • CSE 543- Deep Learning
  • CSE 544 - Principles of Database Systems
  • CSE 546 - Machine Learning
  • CSE 573 - Artificial Intelligence I
  • CSE 583- Software Development for Data Scientists
  • CSE 599D-Theoretical Deep Learning
  • CSE 599I (Spring 2022) Theoretical Deep Learning
  • CSE M 547-Natural Language Processing
  • CSE M 552/ CSE 452- Distributed Systems
  • CSSS 512 - Time Series and Panel Data for the Social Sciences
  • CSSS 526-Structural Equation Models for the Social Sciences
  • CSSS 533- Research Methods in Demography
  • CSSS 544-Bayesian Statistical Methods
  • CSSS 554-Statistical Methods for Spatial Data
  • CSSS 563-Statistical Demography
  • CSSS 569-Visualizing Data
  • CSSS 589-Multivariate Data Analysis for the Social Sciences
  • CSSS 592-Applied Longitudinal Data Analysis for Social Sciences
  • ECON 586- Advanced Applied Time Series Analysis
  • EDPSY 575 - Structural Equation Modeling
  • EE 578/ME 578 - Convex Optimization
  • GEN 540-Introduction to Computational Molecular Biology: Genome and Protein Sequence Analysis
  • GEN 562- Population Genetics
  • IND E 512- Introduction to Optimization Models
  • IND E 524 - Robust Design for Process Improvement
  • MATH 408-Non-Linear Optimization
  • MATH 514-Networks and Combinatorial Optimization
  • MATH 515 - Optimization: Fundamentals and Applications 
  • MATH 524- Real Analysis
  • MATH 574-Fundamental Concepts of Analysis (Not recommended, contact MS advisor if you are interested in taking the course)
  • MATH 575- Fundamental Concepts of Analysis (Not recommended, contact MS advisor if you are interested in taking the course)
  • MATH 582 - Special Topics
  • ME 574 - Introduction to Applied Parallel Computing for Engineers
  • ME 578/EE 578 - Convex Optimization
  • MKTG 596- Adaptive Experimentation in Practice
  • QERM 514 - Analysis of Ecological and Environmental Data
  • SOC 513-Demography and Society
  • SOC 530-Urbanism and Urbanization
  • SOC 531-Fertility and Mortality
  • SOC 533-Research Methods in Demography
  • STAT 491-Introduction to Stochastic Processes
  • STAT 493-Stochastic Calculus for Option Pricing
  • STAT 516-Stochastic Modeling of Scientific Data
  • STAT 522-Advanced Probability
  • STAT 524- Design of Medical Studies
  • STAT 527-Nonparametric Regression and Classification
  • STAT 529-Sample Survey Techniques
  • STAT 533/ BIOST 533- Theory of Linear Models
  • STAT 535-Statistical Learning: Modeling, Prediction, and Computing
  • STAT 536-Analysis of Categorical and Count Data 
  • STAT 538- Statistical Learning: Modeling, Prediction, and Computing
  • STAT 544-Bayesian Statistical Methods
  • STAT 548-Machine Learning for Big Data
  • STAT/BIOST 550-Statistical Genetics I: Mendelian Traits
  • STAT/BIOST 551-Statistical Genetics II: Quantitative Traits
  • STAT/BIOST 552- Statistical Genetics III: Design and Analysis
  • STAT 554-Statistical Methods for Spatial Data 
  • STAT 559 - Measure Theory
  • STAT 560- Hierarchical Modeling for the Social Sciences 
  • STAT 564- Bayesian Statistics for the Social Sciences
  • STAT 566- Causal Modeling
  • STAT 567- Statistical Analysis of Social Networks
  • STAT 591 - Special Topics in Statistics (only graded special topics will be approved)

Denied Elective Courses

  • BIOST 405-Introduction to Health Data Analysis
  • BIOST 546 - Machine Learning for Biomedical and Public Health Big Data
  • BIOST 561- Computational Skills for Biostatistics I
  • CFRM 410- Probability and Statistics for Computational Finance
  • CFRM 420- Introduction to Computational Finance and Financial Econometrics
  • CFRM 425-R Programming for Quantitative Finance
  • CHEM E 556 - Colloidal Systems
  • CSE/STAT 416- Introduction to Machine Learning
  • CSE 446- Machine Learning
  • CSE 515 - Statistical Methods in Computer Science
  • HSERV 558 - Tobacco and Public Health: Prevention, Treatment, Policy and Social Change
  • IMT 543-Relational Database Management Systems
  • MATH 510- Seminar in Algebra
  • PHYS 567 - Theory of Solids
  • SOC 505-Applied Social Statistics
  • SOC 506 - Methodology: Quantitative Techniques in Sociology
  • STAT 435-Introduction to Statistical Machine Learning
  • STAT 509-Econometrics I: Introduction to Mathematical Statistics
  • STAT 572- Preparation for research preliminary