Degree Requirements
Data Analytics Major
The major in Data Analytics (DA) requires a minimum of 46 credits of coursework and an approved summer experience. The detailed requirements are organized in three parts, as follows.
(a) First, students must complete the following 34 credits of core coursework:
Code | Title | |
---|---|---|
DA 101 | Introduction to Data Analytics | |
CS 109 | Discovering Computer Science | |
or CS 111 | Discovering Computer Science: Scientific Data and Dynamics | |
or CS 112 | Discovering Computer Science: Markets, Polls, and Social Networks | |
MATH 135 | Single Variable Calculus | |
or MATH 145 | Multi-variable Calculus | |
DA 200 | Data Analytics Colloquium (once as a sophomore and once as a junior or senior, 2 credits total) | |
DA 210/CS 181 | Data Systems | |
DA/MATH 220 | Applied Statistics | |
DA 301 | Practicum in Data Analytics | |
DA 351 | Advanced Descriptive Methods in Data Analytics | |
or DA 352 | Advanced Predictive Methods in Data Analytics | |
or DA 353 | Advanced Prescriptive Methods in Data Analytics | |
DA 401 | Seminar in Data Analytics |
(b) Second, students must complete a DA summer experience (internship or research project). This experience must be approved by the Data Analytics Program Committee, and is normally undertaken during the summer before the senior year.
(c) Third, students must acquire some depth in a domain of Data Analytics. They will then carry this disciplinary knowledge into their summer experience and senior seminar. Students may satisfy this requirement in one of two ways. First, they may choose to take the designated set of courses from one of the following departments.
Code | Title | |
---|---|---|
Anthropology and Sociology (3 courses) | ||
Only students who matriculated prior to the Fall of 2023 may choose to graduate with an Anthropology/Sociology (ANSO) Data Analytics Concentration. The ANSO Data Analytics Concentration is not offered to students who matriculated Fall 2023 or thereafter. | ||
ANSO 100 | People, Culture and Society | |
ANSO 343 | Demography of Africa | |
OR any ANSO 300-level course pending approval by DA chair | ||
ANSO 351 | Survey Research Methods | |
Biology (4 courses) | ||
BIOL 210 | Molecular Biology and Unicellular Life | |
BIOL 220 | Multicellular Life | |
BIOL 230 | Ecology and Evolution | |
and one of the following: | ||
BIOL 345 | Eukaryotic Cell Biology (Dr. Yoo only) | |
BIOL 350 | Genomics | |
BIOL 356 | Special Topics (Biostatistics) | |
Economics (4 courses) | ||
ECON 101 | Introductory Macroeconomics | |
ECON 102 | Introductory Microeconomics | |
ECON 302 | Intermediate Microeconomic Analysis | |
ECON 467 | Econometrics II (requires ECON 307 or DA 220/MATH 220) | |
Earth and Environmental Sciences (4 courses) | ||
EESC 111 | Planet Earth | |
Either | ||
EESC 234 | Applied GIS for Earth and Environmental Sciences | |
Or | ||
EESC 222 & EESC 223 | Geographic Information Systems I and Geographic Information Systems II | |
And one of the following: | ||
EESC 200 | Environmental Geology | |
EESC 210 | Historical Geology | |
EESC 211 | Rocks, Minerals & Soils | |
And one of the following: | ||
EESC 300 | Geomorphology | |
EESC 310 | Global Biogeochemical Cycles | |
EESC 311 | Structural Geology | |
EESC 313 | Environmental Hydrology | |
EESC 314 | Sedimentology & Stratigraphy | |
EESC 333 | Stable Isotopes in the Environment | |
Sustainability & Environmental Studies (4 courses) | ||
SES 100 | Introduction to Sustainability and Environmental Studies | |
SES 200 | Environmental Analysis | |
And one of the following: | ||
SES 215 | Renewable Energy Systems | |
EESC 234 | Applied GIS for Earth and Environmental Sciences | |
SES 222 & SES 223 | Geographic Information Systems I and Advanced GIS | |
SES 240 | Environmental Politics and Decision-Making | |
SES 274 | Ecosystem Management | |
And one of the following: | ||
SES 256 | Farmscape: Visual Immersion in the Food System | |
SES 262 | Environmental Dispute Resolution | |
SES 264 | Environmental Planning and Design | |
SES 334 | Sustainable Agriculture | |
Philosophy (3 courses) | ||
PHIL 121 | Ethics: Philosophical Considerations of Morality | |
or PHIL 126 | Social and Political Philosophy | |
PHIL 205 | Logic | |
PHIL 210 | Philosophy of Science | |
Physics (3 courses) | ||
Either: | ||
PHYS 121 & PHYS 122 | General Physics I and General Physics II | |
Or | ||
PHYS 125 & PHYS 126 & PHYS 127 | Physics I: Quarks to Cosmos and Physics II: Mechanics, Fluids, and Heat and Physics III: Electricity, Magnetism, Waves, and Optics | |
PHYS 312 | Experimental Physics | |
Psychology (3 courses) | ||
PSYC 100 | Introduction to Psychology | |
PSYC 200 | Research Methods and Statistics | |
PSYC 2XX/3XX | Psychology elective (except research courses, 370, 410, 361-364, 451-452) |
Alternatively, a student may submit an individualized 3-4 course domain elective plan, which must include at least one analytics-intensive course, to be considered for approval by the Data Analytics Program Committee. A successful one-page proposal will clearly describe the student’s desired learning goals and how the proposed courses together achieve these goals. The proposal should also demonstrate the feasibility of completing the proposed courses in the time remaining before graduation. Proposals must be submitted prior to the end of the sophomore year.
Additional Points of Interest
Data Analytics majors wishing to study abroad should do so in the spring semester of their junior year. Data Analytics courses are not normally taken at other institutions, although on rare occasions, a suitable substitute may be found for DA 350 - Advanced Methods for Data Analytics.
If a student uses AP credit to skip a course in their chosen domain area, that course must be replaced with a suitable substitute, determined in cooperation with the appropriate department.
We recommend that students who wish to acquire deeper technical skills in data analytics and/or prepare for graduate work in data science, take additional courses in Mathematics and Computer Science. In Mathematics, students should begin by taking MATH 145 - Multi-variable Calculus and MATH 213 - Linear Algebra and Differential Equations. In Computer Science, students may take CS 173 - Intermediate Computer Science, CS 234 - Mathematical Foundations of Computer Science, and CS 271 - Data Structures. Beyond these, students may pursue additional advanced courses such as
Code | Title |
---|---|
CS 337/MATH 415 | Operations Research |
CS 339 | Artificial Intelligence |
CS 377 | Database Systems |
MATH 425 | Applied Probability |
MATH 435 | Mathematical Modeling |
Students may also pursue a minor or second major in Computer Science or Mathematics. Due to some course overlaps, these options require only 6-7 additional courses.