MS Application Area Courses

Business* and Social Science

  • CIS 417: Introduction to Business Analytics* (Fall A)
  • CIS 418: Advanced Business Modeling and Analytics* (Fall B)
  • CIS 431: Big Data* (Spring B)
  • CIS 432: Machine Learning for Business Analytics* (Spring A) (formerly Predictive Analytics/Python*
  • CIS 433: AI and Deep Learning* (Spring B)
  • CIS 434: Social Media Analytics* (Spring B)
  • CIS 438: Agentic AI* (Spring B)
  • FIN 418: Quantitative Finance w/ Python* (Spring B)
  • GBA 436R: Predictive & Casual Analytics using R* (Fall B)
  • GBA 468P: Prescriptive Analytics w/ Python* (Spring A)
  • GBA 478: AI & Business* (Spring B)
  • GBA 479:  Generative AI for Business Applications* (Spring A)
  • MKT 412: Marketing Research* (Spring B)
  • MKT 437: Digital Marketing Strategy* (Spring A)
  • MKT 440: Pricing Analytics* (Spring A)
  • MKT 451: Consumer and Brand Research* (Spring B)
  • PSCI 404: Probability and Inference (fall)
  • PSCI 405: Linear Models (spring)
  • PSCI 504: Causal Inference (spring)
  • PSCI 505: Maximum Likelihood Estimation (fall)

* Indicates courses in the business and social science application area that are housed in the Simon Business School which do not run on the full semester system and are offered at a different credit hour rate than courses in the School of Arts and Sciences and the Hajim School of Engineering and Applied Science.

Computational Methods

  • DSCC 401: Tools for Data Science (fall/spring)
  • DSCC 402: Data Science at Scale (spring)
  • DSCC 410: Digital Imaging (spring)
  • DSCC 435: Optimization for Machine Learning (fall)
  • DSCC 449: Computer Models of Perception and Cognition (spring)
  • DSCC 463: Dana Management Systems (spring)
  • DSCC 475: Time Series Analysis and Forecasting in Data Science (fall)
  • DSCC 511: Large Language Models (new in Fall 2024)
  • CSC 412: Human Computer Interaction (spring)
  • CSC 442: Artificial Intelligence (fall)
  • CSC 444: Machine Reasoning (fall)
  • CSC 445: Deep Learning (fall)
  • CSC 446: Machine Learning (fall/spring)
  • CSC 447: Natural Language Processing (spring)
  • CSC 449: Machine Vision (spring)
  • CSC 452: Computer Organization (fall/spring)
  • CSC 458: Parallel and Distributed Systems (spring)
  • CSC 460: Technology and Climate Change (spring - not offered in 2026)
  • CSC 463: Data Management Systems (spring)
  • CSC 464: Computer Audition (fall)
  • CSC 466: Frontiers in Deep Learning (spring)
  • CSC 474: Quantum Information Processing
  • CSC 477: End-To-End Deep Learning (fall)
  • CSC 482: Design and Analysis of Efficient Algorithms (fall/spring)
  • CSC 486: Computational Complexity (spring - not offered in 2026)
  • CSC 489: Algorithmic Game Theory (spring)
  • CSC 576: Advanced Topics in Data Management
  • CSC 577: Advanced Topics in Computer Vision
  • CSC 592: Mobile Visual Computing
  • PSYC 519: Data Analysis II - General Linear Approaches (spring)
  • BST 421W/STAT 221W: Sampling Techniques (fall)
  • ECE 408: The Art of Machine Learning (spring)
  • ECE 410: Introduction to Augmented and Virtual Reality (fall)
  • ECE 411: Selected Topics in Augmented and Virtual Reality (spring)
  • ECE 417: Introduction to Dip Using Python
  • ECE 477/CSC 464: Computer Audition (fall)
  • EESC 410: Stochastic Inverse Modeling in Geophysics (spring)
  • EESC 414: Earth Science Data Analysis (fall)
  • EESC 421: Quantitative Environmental Problem Solving 
  • LING 424: Intro to Computational Linguistics 
  • LING 450: Data Sciences for Linguistics
  • LING 470: Tools for Language Documentation
  • LING 481: Statistical and Neural Methods for Computational Linguistics (spring)
  • LING 482: Deep Learning Methods in Computational Linguistics (fall)

Genomics

  • BST 434: Genomic Data Analysis (spring)
  • BIOL 453: Computational Biology (spring)
  • BIOL 457L: Applied Genomics with Lab (fall)
  • IND 501: SMD Research Ethics (1 credit)

Health and Biomedical Sciences

  • BIOL 453: Computational Biology (spring)
  • BIOL 457L: Applied Genomics with Lab (fall)
  • BST 432: High Dimensional Data Analysis (SMD) (fall)
  • BST 434: Genomic Data Analysis (spring) (SMD)
  • BST 467: Applied Statistics in the Biomedical Sciences (SMD) (spring)
  • BST 550: Topics in Data Analysis (SMD) (fall 2024)
  • BCSC 547: Introduction to Computational Neurosciences (every other spring)
  • BCSC 512: Computational Methods in Cog Sci (spring)
  • BCSC 513: Introduction to fMRI (not offered 2021)
  • CSPS 504/BCSC 510: Data Analysis I
  • MHB 401: Data Ethics in Healthcare (SMD)
  • PM 410: Introduction to Data Management/Analysis (SMD) (fall/spring)
  • PM 416: Epidemiologic Methods (SMD) (spring)
  • PM 421: US Health Care System (SMD)(fall)
  • PM 422: Quality of Care and Risk Adjustment (SMD)(spring)
  • PM 431: Advanced Methods in Health Services Research (SMD) (fall)

SMD = courses offered by the School of Medicine and Dentistry

Statistical Methodology

  • STAT 416: Intermediate Statistical Methodology (formerly Applied Statistical Methods-I) (fall)
  • STAT 417: Advanced Statistical Methodology (formerly Applied Stat Methods II) (spring)
  • STAT 418: Categorical Data Analysis (fall)
  • STAT 419: Nonparametric Inference (fall)
  • STAT 423: Bayesian Inference (spring)
  • STAT 476: Statistical Computing in R (formerly Statistical Inference in R) (spring)
  • STAT 477: Introduction to Statistical Software (fall)
  • ECE 440: Introduction to Random Processes (fall)
  • ECE 441: Detection Estimation Theory (spring)
  • ECE 442: Network Science Analytics (spring)
  • ECE 443: Probabilistic Models for Inference Estimation
  • PHYS 403: Modern Statistics and Exploration of Large Data Sets (spring)
  • PHYS 525: Complexity and Network Theory (fall)

 

Course offerings updated as of October 2025