Electives and capstone courses for DS-Eng
Electives and capstone courses
As indicated in the DS-Eng Program Guide, the Data Science program requires elective and capstone courses. Current courses in these categories are listed here:
Data Science Advanced Technical Electives
Data Science Application Electives
Data Science Capstone Courses
Data Science Flexible Technical Electives
Note: There is overlap between the lists of approved Advanced Technical Electives, Application Electives, and Capstone courses. Students may not double-count a course in multiple categories. Additionally, students should consult with online course guides and the departments offering the following courses for questions regarding course availability and eligibility for enrollment.
Approved data science advanced technical electives
BIOINF 527: Introduction to Bioinformatics & Computational Biology
IOE 310: Introduction to Optimization Methods
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 444: Analysis of Societal Networks
EECS 445: Introduction to Machine Learning
EECS 467: Autonomous Robotics
EECS 476: Data Mining
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
EECS 505: Computational Data Science and Machine Learning
IOE 460: Decision Analysis
IOE 465: Design of Experiments
IOE 466: Statistical Quality Control
IOE 474: Simulation
IOE 491, Section 77 only (Winter 2016 only): Constraint Programming
MATH 420: Advanced Linear Algebra
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: Introduction to Statistical Computing
STATS 415: Data Mining
STATS 425: Introduction to Probability
STATS 426: Introduction to Theoretical Statistics
STATS 430: Applied Probability
STATS 449: Topics in Biostatistics
STATS 451: Introduction to Bayesian Data Analysis
STATS 470: Introduction to Design of Experiments
STATS 480: Survey Sampling Techniques
STATS 485: Capstone Seminar
STATS 509: Statistical Models and Methods for Financial Data
STATS 531: Analysis of Time Series
STATS 548: Computations in Probabilistic Modeling in Bioinformatics
Approved data science application electives
AOSS 420: Environmental Ocean Dynamics
AOSS 477: Space Weather Modeling
ASTRO 361: Astronomical Techniques
BIOINF 527: Introduction to Bioinformatics & Computational Biology
BIOINF 551: Proteome Informatics
CLIMATE 410: Earth System Modeling
CLIMATE 462: Instrumentation for Atmospheric and Space Sciences
CLIMATE 475: Earth System Interactions
CLIMATE 476: Ocean Dynamics and Climate
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
ECON 452: Introduction to Econometrics
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 444: Analysis of Societal Networks
EECS 467: Autonomous Robotics
EECS 476: Data Mining
IOE 413: Optimization Modeling in Health Care
IOE 437: Automatic Human Factors
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
STATS 545: Data Analysis in Molecular Biology
STATS 547: Probabilistic Modeling in Bioinformatics
STATS 548: Computations in Probabilistic Modeling in Bioinformatics
Approved data science capstone courses
EECS 442: Computer Vision
EECS 476: Data Mining (WN2020 and WN2021 only)
EECS 486: Information Retrieval & Web Search
STATS 485: Capstone Seminar
STATS 489: Independent Study, Statistics Subject Area
EECS 499: Independent Study, Computer Science Subject Area
Some EECS special topics courses (398, 498, 598) are approved on a term-by-term basis for use as the DS Capstone. See this page for current offerings and approvals.
Multidisciplinary Design Program courses with projects directly related to Data Science may be approved for use as a DS Capstone by the DS-Eng Chief Program Advisor. See the MDP homepage for more information about the program. Some MDP projects are pre-approved for use as the DS Capstone on a term-by-term basis. For those not pre-approved, students should follow the approval process instructions below.
If a course project not on the above list has substantial data science components, students may seek approval to use the course as the Capstone. A project that is focused on software development is likely insufficient unless there is also substantial data analysis or work on other data issues. Students should seek a preliminary read on the suitability of the course by submitting a project proposal to dsengadvisor@umich.edu at the beginning of the course. Students must submit a final project report and a cover letter at the end of the course to dsengadvisor@umich.edu, pointing out the main data science features of the project. This approval process may be used for established courses as well as independent study courses. Please note that no project is guaranteed approval.
Approved data science flexible technical electives
Courses approved as advanced technical electives are automatically approved for use as flexible DS technical electives (however, as noted above, cannot be double-counted between categories). See the Approved Data Science Advanced Technical Electives. Additional approved DS Flexible Technical Electives courses are listed below.
Directed Study Rule: Only 4 hours of directed/independent study or research courses (total across all departments, i.e. EECS, IOE, Civil, etc.) can count toward flexible tech electives. EECS 499 is only open to seniors; sophomores and juniors should consider EECS 399 (can count toward flexible tech electives only if enrolled in FA14 or later).
Aerospace Engineering
AEROSP 215: Introduction to Solid Mechanics and Aerospace Structures
AEROSP 225: Introduction to Gas Dynamics
AEROSP 245: Performance of Aircraft and Spacecraft
Any AEROSP course at the 300-level or higher [AEROSP 390 & 490: see Directed Study Rule above.]
Astronomy
ASTRO 404: Galaxies and the Universe
Bioinformatics
BIOINF 501: Mathematical Foundations for Bioinformatics
Biology
BIOLOGY 305: Genetics
Any BIOLOGY course at the 400-level or higher
Biomedical Engineering
BIOMEDE 221: Biophysical Chemistry and Thermodynamics
BIOMEDE 231: Introduction to Biomechanics
Any BIOMEDE course at the 300-level or higher [BIOMEDE 490: see Directed Study Rule above.]
Chemical Engineering
CHE 230: Material and Energy Balances
Any CHE course at the 300-level or higher [except CHE 405. CHE 490: see Directed Study Rule above.]
Chemistry
CHEM 210: Structure and Reactivity I
CHEM 211: Investigations in Chemistry
CHEM 215: Structure and Reactivity II
CHEM 216: Synthesis and Characterization of Organic Compounds
CHEM 230: Physical Chemical Principles and Applications
CHEM 241: Introduction to Chemical Analysis
CHEM 242: Introduction to Chemical Analysis Laboratory
CHEM 260: Chemical Principles
Any CHEM course at the 300-level or higher [CHEM 398, 399, 498, & 499: see Directed Study Rule above.]
Civil and Environmental Engineering
CEE 211: Statics and Dynamics
CEE 212: Solid and Structural Mechanics
CEE 230: Energy and Environment
CEE 265: Sustainable Engineering Principles
Any CEE course at the 300-level or higher (except 303) [CEE 490: see Directed Study Rule above.]
Climate and Space Sciences & Engineering
Any CLIMATE or SPACE course at the 300-level or higher [CLIMATE/SPACE 499: see Directed Study Rule above.]
Complex Systems
CMPLXSYS 270: Agent Based Modeling
Economics
ECON 409: Game Theory
ECON 452: Introduction to Econometrics
Electrical Engineering and Computer Science
EECS 201: Computer Science Pragmatics
EECS 215: Introduction to Electronic Circuits
EECS 216: Introduction to Signals and Systems
EECS 230: Electromagnetics I
EECS 250: Electronic Sensing Systems (taken WN17 or before)
EECS 270: Introduction to Logic Design
EECS 285: A Programming Language or Computer System
EECS 370: Introduction to Computer Organization
EECS 376: Foundations of Computer Science
Any EECS course at the 300-level or higher (except 398*, 402, 406, 410, and 498*) [EECS 399 (FA’14 or later)/499: see Directed Study Rule above.] EECS departmental credit at the 300- or 400-level (301X, 401X, etc.) can be used as FTE credit. *Each special topics course is reviewed for possible FTE/ULCS credit for the term/topic offered; see the Advising Office for details.
Engineering
ENGR 350: International Lab. Experience for Engineers [See Directed Study Rule above.]
ENGR 355: Multidisciplinary Design I [See Directed Study Rule above.]
ENGR 403: Scientific Visualization
ENGR 450: Multidisciplinary Design [See Directed Study Rule above.]
ENGR 455: Multidisciplinary Design II [See Directed Study Rule above.]
ENGR 480: Global Synthesis Project (Tauber Institute) [See Directed Study Rule above.]
Entrepreneurship
ENTR 390 (section 013 only): TechLab MCity [See Directed Study Rule above.]
Industrial and Operations Engineering
IOE 202: Operations Modeling (course is not open to students with 85 credits or more)
Any IOE course at the 300-level or higher (except 373 & 422) [IOE 490: see Directed Study Rule above.]
Linguistics
LING 442: Computational Linguistics II
Materials Science and Engineering
MATSCIE 220: Introduction to Materials and Manufacturing
MATSCIE 242: Physics of Materials
MATSCIE 250: Principles of Engineering Materials
Any MATSCIE course at the 300-level or higher [MATSCIE 490: see Directed Study Rule above.]
Mathematics
MATH 216: Introduction to Differential Equations
MATH 297: Introduction to Analysis
Any MATH course at the 300-level or higher (except 310, 327, 333, 385, 389, 399, 417, 419, 422, 429, 431, 485, 486, 489, 497)
Mechanical Engineering
MECHENG 211: Introduction to Solid Mechanics
MECHENG 235: Thermodynamics
MECHENG 240: Introduction to Dynamics and Vibrations
MECHENG 250: Design and Manufacturing I
Any MECHENG course at the 300-level or higher [MECHENG 490 & 491: see Directed Study Rule above.]
Molecular, Cellular, and Developmental Biology (MCBD)
MCDB 306: Introductory Genetics Laboratory
MCDB 310: Introductory Biochemistry
Naval Architecture and Marine Engineering
NAVARCH 260: Marine Systems Manufacturing
NAVARCH 270: Marine Design
Any NAVARCH course at the 300-level or higher [NAVARCH 490: see Directed Study Rule above.]
Nuclear Engineering and Radiological Sciences
NERS 250: Fundamentals of Nuclear Engineering and Radiological Sciences
Any NERS course at the 300-level or higher [NERS 499: see Directed Study Rule above.]
Operations and Management Science
OMS 605: Manufacturing and Supply Operations
Performing Arts Technology
PAT 452: Interactive Music Design II
PAT 462: Digital Sound Synthesis
Philosophy
Physics
Any PHYSICS course at the 300-level or higher (except 333, 334, 420, and 481). [PHYS 496, 497, 498, 499: see Directed Study Rule above.]
School of Information
SI 301: Models of Social Information Processing
SI 364: Building Interactive Applications
SI 422: Evaluation of Systems and Services
SI 630: Natural Language Processing: Algorithms and People
Statistics
STATS 401: Applied Statistical Methods II
STATS 403: Introduction to Quantitative Research Methods
STATS 406: Computational Methods in Statistics and Data Science
STATS 430: Applied Probability
STATS 470: Introduction to the Design of Experiments
Any statistics class at 500-level or 600-level except for seminar and independent study courses.
Technology & Operations (Ross School of Business)
TO 414: Advanced Analytics For Management Consulting
TO 605: Manufacturing and Supply Operations