Data Science, Bachelor of Science

The Bachelor of Science in Data Science (BSDS) is interdisciplinary and requires the effective integration of three components to produce meaningful results. The three components include 1) the domain that provides the data, 2) statistics for analysis, modeling, and inference, and 3) computer science for data access, management, protection, as well as effective processing in modern computer architectures. This degree prepares graduates for a myriad of opportunities to work in and advance their data science careers.

Program Outcomes

The Bachelor of Science in Data Science will prepare students to:

Integrate foundational knowledge of all areas of data science (General Data Science Knowledge).

Apply fundamental principles and practices of data science (Data Science Principles and Practices)

Apply critical and ethical thinking to solve problems in data science (Critical and Ethical Thinking).

Evaluate data to inform decisions and solve problems in data science (Quantitative Literacy).

Create the ability to develop and express ideas while applying a variety of delivery models, genres, and styles (Communication).

Collaborate effectively on diverse teams to accomplish a common goal (Collaboration).

Admission Requirements

City University of Seattle's undergraduate admission requirements, found under Admissions in the catalog menu, apply to this program. 

Total Required Credits (180 Credits)

*This program requires CS 251 Statistical Computing or Math 107 or above to meet the QSR requirement. 

Preparatory Course (15 Credits)

IS 201Fundamentals of Computing

5

CS 132Computer Science I

5

CS 251Statistical Computing (QSR for select programs/NS)

5

Core Requirements (45 Credits)

CS 302Human Computer Interaction

5

CS 330Network Communications

5

CS 351Discrete Mathematics in Computing (NS)

5

IS 312Web Design

5

IS 340Operating Systems

5

IS 345Cybersecurity

5

IS 350Systems Analysis and Design

5

IS 360Database Technologies

5

IS 471Cyber Ethics (SS)

5

Data Science (30 Credits)

CS 476Data Analysis and Presentation

5

CS 469Data Structures and Algorithms in Computing

5

CS 475Artificial Intelligence

5

CS 483Mathematics for Machine Learning

5

CS 479Data Mining and Machine Learning

5

CS 484Big Data Systems

5

Upper Division Electives (10 credits)

Choose two classes from the list below.

IS 470IT Service Management

5

IS 472IT Compliance

5

IS 456Database Systems Management

5

IS 457Enterprise Systems

5

CS 481Network Security

5

CS 487Data Security

5

CS 493Technology and Computing Internship

5

Capstone (5 Credits)

CS 497Technology and Computing Capstone

5