Electives
Electives
The following courses have been approved to satisfy the elective requirements for the Data Science Minor. You may choose electives from any of the departments listed.
Some things to keep in mind:
- Some of the courses that can be used as electives have prerequisites or corequisites that may or may not be part of the minor.
- Your choice on how to satisfy the core requirements may also influence which electives you can take, since departments may only consider some of the options as valid prerequisites.
- Departments may have registration limits for students not in their majors, and/or may require you to join a waitlist prior to allowing you to enroll.
- BCB 555 – Bioalgorithms
- BIOL 525/525L – Analysis and Interpretation of Sequence-Based Functional Genomics Experiments
- BIOL 534 – Mathematical Modeling in the Life Sciences
- BIOL 553 – Mathematical and Computational Models in Biology
- BIOL 554 – Introduction to Computational Neuroscience
- BIOL 562 – Statistics for Environmental Scientists
- BIOL 563 – Statistical Analysis in Ecology and Evolution
- BMME 576 – Mathematics for Image Computing
- CLAR 411 – Archaeological Field Methods
- COMP 210 – Data Structures and Analysis
- COMP 388 – Advanced Cyberculture Studies
- COMP 410 – Data Structures
- COMP 421 – Files and Databases
- COMP 426 – Modern Web Programming
- COMP 433 – Mobile Computing Systems
- COMP 486 – Applications of Natural Language Processing
- COMP 487 – Information Retrieval
- COMP 488 – Data Science in the Business World
- COMP 555 – Bioalgorithms
- COMP 560 – Artificial Intelligence
- COMP 562 – Introduction to Machine Learning
- COMP 572 – Computational Photography
- COMP 576 – Mathematics for Image Computing
- ECON 470 – Econometrics
- ECON 545 – Advanced Industrial Organization
- ECON 550 – Advanced Health Econometrics
- ECON 565 – Research in Development Economics
- ECON 571 – Advanced Econometrics
- ECON 573 – Machine Learning and Econometrics
- ECON 575 – Applied Time Series Analysis and Forecasting
- ECON 580 – Advanced Labor Economics
- ENEC 305 – Data Analysis and Visualization of Social and Environmental Interactions
- ENEC 437 – Social Vulnerability to Climate Change
- ENEC 468 – Temporal GIS and Space/Time Geostatistics for the Environment and Public Health
- ENEC 562 – Statistics for Environmental Scientists
- ENEC 563 – Statistical Analysis in Ecology and Evolution
- ENVR 468 – Temporal GIS and Space/Time Geostatistics for the Environment and Public Health
- EPID 600 – Principles of Epidemiology for Public Health
- EXSS 327 – Predictive Analytics in Sport
- GEOG 370 – Introduction to Geographic Information
- GEOG 392 – Research Methods in Geography
- GEOG 414 – Climate Change
- GEOG 416 – Applied Climatology: The Impacts of Climate and Weather on Environmental and Social Systems
- GEOG 437 – Social Vulnerability to Climate Change
- GEOG 446 – Geography of Health Care Delivery
- GEOG 456 – Geovisualizing Change
- GEOG 491 – Introduction to GIS
- GEOL 520 – Data Analysis in the Earth Sciences
- HIST 273 – Water, Conflict, and Connection in the Middle East
- LING 202 – Linguistic Variation and Language Change
- LING 203 – Language Acquisition and Development
- LING 333 – Human Language and Animal Communication Systems
- LING 401 – Language and Computers
- LING 422 – Research Methods in Phonetics and Laboratory Phonology
- LING 520 – Linguistic Phonetics
- LING 525 – Introduction to Historical and Comparative Linguistics
- MASC 561 – Time Series and Spatial Data Analysis
- POLI 381 – Data in Politics II: Frontiers and Applications
- ROML 501 – Introduction to Digital Humanities for Romance Languages, Cultures, and Heritage Studies
* Planned courses for 2024-2025.
Choosing your Electives
If you are a student at Carolina thinking of declaring Data Science as your minor, you have many options for choosing the two electives needed to complete the program. Since many departments offer courses that can be used as electives for the minor, we have created an interactive tool to help you select the ones that best fit your interests.