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:

DA 101Introduction to Data Analytics
CS 109Discovering Computer Science
or CS 111 Discovering Computer Science: Scientific Data and Dynamics
or CS 112 Discovering Computer Science: Markets, Polls, and Social Networks
MATH 135Single Variable Calculus
or MATH 145 Multi-variable Calculus
DA 200Data Analytics Colloquium (once as a sophomore and once as a junior or senior, 2 credits total)
DA 210/CS 181Data Systems
DA/MATH 220Applied Statistics
DA 301Practicum in Data Analytics
DA 350Advanced Methods for Data Analytics
DA 401Seminar 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.

Anthropology and Sociology (3 courses)
ANSO 100People, Culture and Society
ANSO 343Demography of Africa
OR any ANSO 300-level course pending approval by DA chair
ANSO 351Survey Research Methods
Biology (4 courses)
BIOL 210Molecular Biology and Unicellular Life
BIOL 220Multicellular Life
BIOL 230Ecology and Evolution
and one of the following:
BIOL 309
Computational Biology
BIOL 345
Eukaryotic Cell Biology (Dr. Yoo only)
BIOL 350
Genomics
BIOL 356
Special Topics (Biostatistics)
Economics (4 courses)
ECON 101Introductory Macroeconomics
ECON 102Introductory Microeconomics
ECON 302Intermediate Microeconomic Analysis
ECON 467Econometrics II (requires ECON 307 or DA 220/MATH 220)
Earth and Environmental Sciences (4 courses)
EESC 111Planet 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
Environmental Studies (4 courses)
ENVS 100Integrated Environmental Studies
ENVS 200Environmental Analysis
And one of the following:
ENVS 215
Renewable Energy Systems
EESC 234
Applied GIS for Earth and Environmental Sciences
ENVS 222
ENVS 223
Geographic Information Systems I
and Geographic Information Systems II
ENVS 240
Environmental Politics and Decision Making
ENVS 274
Ecosystem Management
And one the following:
ENVS 236
Political Ecology
ENVS 256
Farmscape: Visual Immersion in the Food System
ENVS 262
Environmental Dispute Resolution
ENVS 284
Environmental Planning and Design
ENVS 334
Sustainable Agriculture
Philosophy (3 courses)
PHIL 121Ethics: Philosophical Considerations of Morality
or PHIL 126 Social and Political Philosophy
PHIL 205Logic
PHIL 210Philosophy of Science
Physics (3 courses)
Either:
PHYS 121
PHYS 122
General Physics I
and General Physics II
Or
PHYS 125
PHYS 126
PHYS 127
Principles of Physics I: Quarks to Cosmos
and Principles of Physics II
and Principles of Physics III
PHYS 312Experimental Physics
Psychology (3 courses)
PSYC 100Introduction to Psychology
PSYC 200Research Methods and Statistics
PSYC 2XX/3XXPsychology 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 ScienceCS 234 - Mathematical Foundations of Computer Science, and CS 271 - Data Structures.  Beyond these, students may pursue additional advanced courses such as

CS 337/MATH 415Operations Research
CS 339Artificial Intelligence
CS 345Parallel Systems and Programming
CS 377Database Systems
MATH 425Applied Probability
MATH 435Mathematical 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.

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