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Data Science Electives

(Note: There is overlap between the lists of approved Advanced Technical Electives, Application Electives, Capstone courses, and Flexible Electives. Students may not double-count a course in multiple categories. Additionally, students should consult with online course guides and departments offering the following courses for questions regarding course availability and eligibility for enrollment.)
 

Approved DS Application Electives

AOSS 410: Earth System Modeling

AOSS 420: Environmental Ocean Dynamics

AOSS 462: Instrumentation for Atmospheric and Space Sciences

AOSS 475: Earth System Interactions

AOSS 476: Ocean Dynamics and Climate

AOSS 477: Space Weather Modeling

ASTRO 361: Astronomical Techniques

BIOINF 527: Introduction to Bioinformatics & Computational Biology

BIOINF 551: Proteome Informatics

CMPLXSYS 510: Introduction to Adaptive Systems

EARTH 408: Introduction to GIS in the Earth Sciences (or GEOG 506; credit for both will not be granted)

EARTH 414: Weather Systems

ECON 409: Game Theory

EEB 315: Ecology and Evolution of Complex Disease

EEB 391: Introduction to Evolution: Quantitative Approach

EEB 408: Modeling for Ecology and Evolutionary Biology

EEB 416: Introduction to Bioinformatics

EEB 430: Modeling Infectious Diseases

EEB 466: Mathematical Ecology

EEB 481: Population Dynamics and Ecology

EECS 442: Computer Vision

EECS 467: Autonomous Robotics

MATH 422: Risk Management and Insurance

MATH 423: Mathematics of Finance

MATH 463: Math Modeling in Biology

MCDB 408: Genomic Biology

POLSCI 490: Game Theory and Formal Models

POLSCI 499: Quantitative Methods of Political Analysis

PSYCH 448: Mathematical Psychology

SI 365: Cyberscience: Computational Science and the Rise of the Fourth Paradigm

SI 429: eCommunities: Analysis and Design of Online Interaction Environments

SI 542: Introduction to Health Informatics

SI 554: Consumer Health Informatics

SI 639: Web Archiving

SI 650: Information Retrieval

STATS 449: Topics in Biostatistics

STATS 509: Statistical Models and Methods for Financial Data (registration priority for this course will given to graduate students whose program requires the class)

STATS 545: Data Analysis in Molecular Biology

STATS 547: Probabilistic Modeling in Bioinformatics

STATS 548: Computations in Probabilistic Modeling in Bioinformatics
 

Approved DS Advanced Technical Electives

BIOINF 527: Introduction to Bioinformatics & Computational Biology

IOE 310: Introduction to Optimization Methods (IOE 202 enforced prerequisite)

EARTH 408: Introduction to GIS in the Earth Sciences (or GEOG 506; credit for both will not be granted)

ECON 409: Game Theory

EECS 388: Introduction to Computer Security

EECS 442: Computer Vision

EECS 445: Machine Learning

EECS 467: Autonomous Robotics

EECS 477: Introduction to Algorithms

EECS 588: Parallel Computing

EECS 482: Operating Systems

EECS 484: Database Management Systems

EECS 485: Web Database and Information Systems

EECS 492: Introduction to Artificial Intelligence

MATH 419: Linear Spaces and Matrix Theory

MATH 451: Advanced Calculus 1

MATH 471: Introduction to Numerical Methods

SI 422: Evaluation of Systems and Services

SI 649: Information Visualization

SI 650: Information Retrieval

STATS 403: Introduction to Quantitative Research Methods

STATS 406: Computational Methods in Statistics and Data Science

STATS 415: Data Mining

STATS 425: Introduction to Probability

STATS 426: Introduction to Theoretical Statistics

STATS 449: Topics in Biostatistics

STATS 451: Introdcution to Bayesian Data Analysis

STATS 470: Introduction to Design of Experiments

STATS 480: Survey Sampling Techniques

STATS 485: Capstone Seminar

STATS 508: Statistical Analysis of Financial Data

STATS 531: Analysis of Time Series

STATS 548: Computations in Probabilistic Modeling in Bioinformatics
 

Approved DS Capstone Courses

EECS 442: Computer Vision

EECS 467: Autonomous Robotics

STATS 485: Capstone Seminar

STATS 489*: Independent Study, Statistics Subject Area

EECS 499*: Independent Study, Computer Science Subject Area

 

*Must secure approval from a Data Science advisor and the supervising faculty mentor in EECS or STATS (depending on subject area elected). Not all independent study projects are approved. Approval must be requested in advance.