How to Read Course Descriptions
The bolded first line begins with a capitalized abbreviation that designates the subject area followed by the course number and title. The unit value is also displayed.
CR/NC: Indicates a course is offered on a Credit/No Credit grading basis only.
GE Area: Indicates the General Education (GE) Area for which the course may fulfill a requirement. See the course description for details.
USCP: Indicates that credit in the course satisfies the U.S. Cultural Pluralism requirement.
GWR: Indicates the course will satisfy the Graduation Writing Requirement, if the student earns a grade of C or better AND receives certification of proficiency in writing based on a 500-word in-class essay.
Term Typically Offered: F = Fall quarter, W = Winter quarter, SP = Spring quarter, SU = Summer quarter
Prerequisite: Coursework to be completed and/or requirements to be met before taking the course
Corequisite: Course or courses that must be taken in a previous term or in the same term
Concurrent: Course or courses that must be taken in the same term
Recommended: Course with supporting content that is recommended, but is not required to be taken in a previous term or in the same term
The course description summarizes the purpose and key topical areas of the course, and includes special requirements if they exist. It indicates the mode of instruction, such as lecture and/or laboratory; if no mode is indicated, the course is supervised independent study. If a course can be taken more than once for credit, the description will indicate that either major credit or total credit is limited to a specified number of units. Some course descriptions end with information about whether the course was "formerly" another course or whether the course is cross-listed. A cross-listed course is the same course offered within multiple subject areas, MCRO/WVIT 301 Wine Microbiology for example.
DATA 301. Introduction to Data Science. 4 units
Introduction to the field of data science and the workflow of a data scientist. Types of data (tabular, textual, sparse, structured, temporal, geospatial), basic data management and manipulation, simple summaries, and visualization. 3 lectures, 1 laboratory.
DATA 401. Data Science. 4 units
Principles of data science and big data analytics. Volume, velocity, and variety of data. Acquisition, processing, and cleaning of large data-sets. Analytics for big data. 3 lectures, 1 laboratory.
DATA 451. Data Science Capstone I. 2 units
Term Typically Offered: W
Prerequisite: DATA 401.
Working with clients to develop data-driven solutions for systems to be constructed in DATA 452. Specification and design requirements, elicitation techniques, research and data gathering methods; project planning, time and budget estimating; project team organization. Ethics and professionalism. 2 laboratories.
DATA 452. Data Science Capstone II. 2 units
Term Typically Offered: SP
Prerequisite: DATA 451.
Team-based design, implementation, deployment and delivery of a system or analytical methodology that involves working with and analyzing large quantities of data. Technical management of research and development teams. Technical documentation, quality assurance, integration and systems testing. Design and conduct of empirical studies. Visualization and presentation of results orally and in writing. 2 laboratories.