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Technical and Domain Science Electives

Advanced Technical and Domain Science Electives Recommended (Pre-approved) Courses

Below is a list of courses pre-approved by the Department of Statistics that satisfy the Data Science major’s technical and/or domain Science electives requirement. If a student or department would like to submit a course for consideration for addition to this list, please contact the Director of Data Science with the course name, description, and a copy of the syllabus.

Please note this list is still being edited. Check back frequently for changes and contact the Director of Data Science with questions.

Technical and Domain Science Electives Recommended (pre-approved) Courses

ANTHRO 322 Introduction to Archaeology Research Design and Methods
ANTHRO 324 Archaeological Survey Methods
ANTHRO 362 Advanced Methods in Quantitative of Analysis
ANTHRO 389 Ethnographic Methods and Analysis

Biological SciencesBIOL_SCI 338 Modeling Biological DynamicsBIOL_SCI 345 Principles & Methods in Systems Biology
BIOL_SCI 378 Functional Genomics

Biomedical Engineering
BMD_ENG 311 Computational Genomics

Chemical and Biological Engineering
CHEM_ENG 379 Computational Biology: Principles & Applications

COMM_ST 371 Cultural Analytics

Computer Science
COMP_SCI 325-1 Artificial Intelligence Programming
COMP_SCI 336 Design & Analysis of Algorithms
COMP_SCI 339 Intro to Databases
COMP_SCI 348 Intro to Artificial Intelligence
COMP_SCI 352 Machine Perception of Music & Audio

Earth and Planetary Science
EARTH 323 Seismology and Earth Structure
EARTH 327 Geophysical Time Series Analysis
EARTH 340 Physics of Weather and Climate
EARTH 343 Earth System Modeling
EARTH 353 Mathematical Inverse Methods in Earth and Environmental Science
EARTH 360 Instrumentation and Field Methods
EARTH 361 Scientific Programming in Python
EARTH 362 Data Analysis for Earth and Planetary Sciences

ECON 381-1,2 Econometrics
ECON 383 Applied Econometrics

Engineering Sciences and Applied Mathematics
ES_APPM 346 Modeling and Computation in Science & Engineering
ES_APPM 370 Introduction to Computational Neuroscience
ES_APPM 375-1,2 Quantitative Biology I: Experiments, Data, Models, and Analysis

Environmental sciences (These courses are also cross-listed in other department EARTH)
ENVR_SCI 390-0-01 GIS Level 1
ENVR_SCI 390-0-02 GIS Level 2
ENVR_SCI 390-0-03 – Topics: R Data Science

Global Health Studies
GBL_HLTH 320 Qualitative Research Methods in Global Health

Industrial Engineering and Management Sciences
IEMS 313 Foundation of optimization
IEMS 336 Stochastic models
IEMS 341 Social network
IEMS 351 Optimization Methods In Data Science
IEMS 365: Analytics for Social Good (Application only & Junior or Senior standing)

Integrated Marketing CertificateIMC 302 Research for Marketing CommunicationsIMC 307 Digital, Social and Mobile MarketingIMC 390 Social Networks

JOUR 377 Data Analysis and Visualization (seats are first reserved for Medill students)

LING 334 Introduction to Computational Linguistics

MATH 306-0 Combinatorics & Discrete Mathematics
MATH 308-0 Graph Theory
MATH 310-2, 3 Probability and Stochastic Processes
MATH 311-2, 3 MENU Probability and Stochastic Processes
MATH 366-0 Mathematical Models in FinanceMATH 368 Introduction to OptimizationMATH 386-1, 2 Econometrics for MMSS

Molecular BioSciences
BIOL_SCI 323 Bioinformatics: Sequence and Structure Analysis
BIOL_SCI 341 Population Genetics

Political Science
POLI_SCI 310 Methods of Political Inference
POLI_SCI 312 Statistical Research Methods

PSYCH 380 Advanced Statistics and Experimental Design
PSYCH 387 Consumer Psychology and Marketing Research

SOC_POL 351 Special Topics (Quantitative Tools)

SOCIOL 303 Analysis and Interpretation of Social Data
SOCIOL 329 Field Research and Methods of Data Collection

STAT 302 Data Visualization
STAT 320-3 Statistical Theory and Methods 3
STAT 328 Causal Inference
STAT 342 Statistical Data Mining
STAT 344 Statistical Computing
STAT 348 Applied Multivariate Analysis
STAT 350 Regression Analysis
STAT 351 Design and Analysis of Experiments
STAT 352 Nonparametric Statistical Methods
STAT 353 Advanced Regression
STAT 354 Applied Time Series Modeling and Forecasting
STAT 356 Hierarchical Linear Models
STAT 365 Introduction to the Analysis of Financial Data
STAT 357 Elementary Bayesian Statistics



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