Requirements Overview

  1. Complete Core Coursework
  2. Complete Data Analytics Summer Experience
  3. Select and Complete Data Analytics Domain 

The detailed requirements for both BA and BS degrees are organized as follows:

Bachelor of Arts

The Bachelor of Arts in Data Analytics (DA) requires a minimum of 46 credits of coursework.

1) 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
or CS 113 Discovering Computer Science: Physical Computing
or CS 114 Discovering Computer Science: Computing for the Social Good
MATH 135Single Variable Calculus
or MATH 145 Multivariable Calculus
DA 200Data Analytics Colloquium (Sophomore, 1 credit)
DA 200Data Analytics Colloquium (Junior or Senior, 1 credit)
DA 210/CS 181Data Systems
DA/MATH 220Applied Statistics
DA 301Practicum in Data Analytics
DA 351Advanced Descriptive Methods in Data Analytics
or DA 352 Advanced Predictive Methods in Data Analytics
or DA 353 Advanced Prescriptive Methods in Data Analytics
DA 401Seminar in Data Analytics

2) Students must complete a DA 030 (summer 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.

3 ) Students must acquire some depth in a domain of Data Analytics. See 'Domains in Data Analytics' for more information.

Bachelor of Science

Students who wish to acquire deeper methodological skills in data analytics and/or better prepare for graduate study may pursue a Bachelor of Science in Data AnalyticsStudents looking for added methodological depth and foundation, or to further strengthen their graduate school readiness, may also wish to pursue a minor or second major in Computer Science, Mathematics, or Applied Mathematics, or in another related quantitative field.

1) Students must complete the following 40 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
or CS 113 Discovering Computer Science: Physical Computing
or CS 114 Discovering Computer Science: Computing for the Social Good
MATH 145Multivariable Calculus
MATH 213Linear Algebra and Differential Equations (recommendation: take by the end of Sophomore year.)
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
Complete two advanced methods in data analytics courses (DA 35X).
DA 351Advanced Descriptive Methods in Data Analytics
or DA 352 Advanced Predictive Methods in Data Analytics
or DA 353 Advanced Prescriptive Methods in Data Analytics
DA 401Seminar in Data Analytics

2) Students must complete an additional methods-based elective course approved by the Data Analytics program. To avoid double-counting elective courses, a course used to satisfy another degree program’s major or minor elective requirement cannot be counted as the methods elective for the Bachelor of Science in Data Analytics. Likewise, a course that is used to satisfy a student’s Data Analytics Domain cannot be counted as the methods elective for the Bachelor of Science in Data Analytics. A full list of currently offered electives that meet this requirement is maintained by the Data Analytics program. Examples include:

DA 271Theory and Practice of Data Visualization
CS 271Data Structures
CS 339Artificial Intelligence
CS 337/MATH 415Operations Research
CS 377Database Systems
ECON 467Econometrics II
MATH 420Statistical Modeling
MATH 422Time Series Analysis
MATH 435Mathematical Modeling


3) Students must complete a DA 030 (summer 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.

4) Students must acquire some depth in a domain of Data Analytics. See 'Domains in Data Analytics' for more information.

Domains in Data Analytics

Students pursuing BA or BS in Data Analytics 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.

  1. They may choose to take the designated set of courses from a specific department (see table below).
  2. They 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 before the end of the sophomore year.
Biology (4 courses)
BIOL 210Molecular Biology and Unicellular Life
BIOL 220Multicellular Life
BIOL 230Ecology 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 101Introductory Macroeconomics
ECON 102Introductory Microeconomics
ECON 302Intermediate Microeconomic Analysis
ECON 307Introductory Econometrics
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
Sustainability & Environmental Studies (4 courses)
SES 100Introduction to Sustainability and Environmental Studies
SES 200Environmental 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 Geographic Information Systems II
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 264Environmental Planning and Design
SES 334
Sustainable Agriculture and Food Systems
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
Physics I: Quarks to Cosmos
and Physics II: Mechanics, Fluids, and Heat
and Physics III: Electricity, Magnetism, Waves, and Optics
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)

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 351/2/3 - 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.