Data Science, B.S.

Data Science is the “science of planning for, acquisition, management, analysis of, and inference from data” [Mathematical Association of America]. The Data Science program will support students to develop and practice skills in synthesizing knowledge, applying contemporary statistics, data analysis, and computational science methods to solve social and environmental problems. At the core of the Data Science experience is a recursive process of obtaining, wrangling, curating, managing, processing, and exploring data, defining questions, performing analyses and communicating the results.

Requirements for the Bachelor’s Degree

A bachelor’s degree requires a total of 120 units. Students must fulfill General Education & All-University Requirements , residency, unit, and GPA requirements as outlined in the Bachelor’s Degree Requirements . This major includes a Graduation Writing Assessment Requirement (GWAR) certified course.

Major Academic Plan, Data Science, B.S.

Program MAPs represent recommended or possible pathways toward degree completion in four years (or two years for transfer students). Please see an advisor and use the DARS planner to create an education plan that is customized to meet your needs.

Data Science, B.S. MAP

Data Science, B.S. Transfer MAP

Requirements for the Major (65-71 Units)

Program Pre-requisite (0-6 Units)

Students may demonstrate calculus readiness by achieving an appropriate score on a department administered placement test, by successful completion of a course in precalculus, or by completing one of the following prerequisite course pathways, or their equivalent:

MATH 101 - College Algebra Units: 3 and
MATH 101T - Trigonometry Units: 3
or
MATH 102 - Algebra and Elementary Functions Units: 4
or
MATH 109B - Calculus 1 Part 1 Units: 5

Lower Division (27 Units)

CS 111 - Computer Science Foundations 1 Units: 4
DATA 111 - Introduction to Programming and Computational Thinking for Data Science Units: 4
DATA 271 - Data Wrangling and Visualization Units: 4
MATH 107 - Introduction to Linear Algebra Units: 3
MATH 109 - Calculus I Units: 4 ^[1]
MATH 110 - Calculus II Units: 4
STAT 109 - Introductory Biostatistics Units: 4
^[1]Complete MATH 109C if MATH 109B was taken previously.

Upper Division (23 Units)

CS 325 - Database Design Units: 4
DATA 311 - Applied Data Analysis Units: 4
DATA 322 - Machine Learning for Data Science Units: 4
DATA 422 - Advanced Data Science Methods and Ethics Units: 4
DATA 450W - Data Science Capstone Units: 3

Upper Division Statistics

Complete one of the following statistics courses.

STAT 323 - Probability Theory and Mathematical Statistics Units: 4
STAT 333 - Linear Regression Models/ANOVA Units: 4
STAT 404 - Multivariate Statistics Units: 4
STAT 406 - Sampling Design and Analysis Units: 4
STAT 410 - Modern Statistical Modeling Units: 4
or advisor approved statistics-related course in an area of application/emphasis.

Area of Application/Emphasis (15 Units)

To fulfill the major requirements, students are expected to gain expertise in an area to which data science may be applied.

The area of application requires an advisor-approved cohesive set of at least 15 units, 9 of which must be upper division level. Students also have the option, with advisor approval, to complete a minor or certificate program to fulfill the area of application/emphasis requirement.

Suggested areas of emphasis include:

Mathematics: For students who desire access to more technically demanding careers requiring extensive knowledge of mathematics.
Biological Sciences: For students who wish to use data science to tackle a diverse set of biological questions in areas ranging from medicine to genomics to evolution.
Business/Economics: For students with career goals that demand specialized business training. This emphasis will help students appreciate how data science methods support business or economic decision-making and can improve products, services, and organizations.
Energy: For students interested in combining engineering and environmental science with data science. Career paths include engineering consulting firms, state or federal policy agencies, and private energy industry firms.
Natural Resources and/or Environmental Planning: For students interested in careers as industry representatives, advocates, consultants, analysts and government planners working on natural resource and/or environmental issues.
Justice: For students interested in careers which critically analyze crime patterns, access to justice, policy, or advocacy.
Political Science: For students interested in using data science to help predict, explain, or analyze political phenomena and behavior.

Program Learning Outcomes

Students completing the program will have demonstrated:

Computational skills to extract different types and quantities of data from multiple sources and create visualizations and other data products for various audiences;
Statistical knowledge to build mathematical models and ensure the validity of data and its analysis;
Domain knowledge in one or more key areas of application to gain domain specific information from data and its analysis and to communicate insights from that data that support understanding of and solutions for critical problems within the domain;
Contemporary computer-based and data-oriented analytical skills and related ethical considerations to support a broad synthesis of knowledge including contributions from humanities, natural sciences, traditional ecological knowledges, and other foundational frameworks for understanding.