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:
Apply fundamental principles and practices of data science (Data Science Principles and Practices)
Integrate foundational knowledge of all areas of data science (General Data Science Knowledge).
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)
Lower – Division Requirements (90 Credits)
Students must meet General Education requirements listed below. This is typically completed within the 90 required lower division credits. See the General Education Requirements section of this catalog for more detailed information.
For this program Quantitative/Symbolic Reasoning is met through the course CS 251 Statistical Computing or an equivalent course.
General Education Requirements
|
Total Credits
|
College Composition II (CCII)
|
5 Credits
|
Quantitative/Symbolic Reasoning (CM/QSR)
|
5 Credits
|
Humanities (HU)
|
15 Credits
|
Social Sciences (SS)
|
15 Credits
|
Natural Sciences (NS)
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15 Credits
|
Pre-Entry Requirement (0 Credit)
Students must take this course in the first quarter of enrollment. Students may take another program requirement concurrently.
CS 100 | STC BS Orientation to Bachelor's Programs | 0 |
Preparatory Courses (15 Credits)
These preparatory courses may be applied towards CityU's General Education and Lower Division credit requirements.
CS 132 | Computer Science I | 5 |
CS 251 | Statistical Computing (QSR for select programs OR NS) | 5 |
IS 201 | Fundamentals of Computing | 5 |
Core Requirements (45 Credits)
Depth of Study: Data Science (30 Credits)
CS 469 | Data Structures and Algorithms in Computing | 5 |
CS 475 | Artificial Intelligence | 5 |
CS 476 | Data Analysis and Presentation | 5 |
CS 479 | Data Mining and Machine Learning | 5 |
CS 483 | Mathematics for Machine Learning | 5 |
CS 484 | Big Data Systems | 5 |
Choice (10 credits)
Information Systems
IS 456 | Database Systems Management | 5 |
IS 457 | Enterprise Systems | 5 |
Information Technology
Cybersecurity
Data Science
IS 410 | Programming in Data Analytics | 5 |
Internship
The internship course is repeatable.
CS 493 | Technology and Computing Internship | 5 |
Capstone (5 Credits)
CS 497 | Technology and Computing Capstone | 5 |