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:
1. Apply fundamental principles and practices of data science (Data Science Principles and Practices)
2. Integrate foundational knowledge of all areas of data science (General Data Science Knowledge).
3. Apply critical and ethical thinking to solve problems in data science (Critical and Ethical Thinking).
4. Evaluate data to inform decisions and solve problems in data science (Quantitative Literacy).
5. Create the ability to develop and express ideas while applying a variety of delivery models, genres, and styles (Communication).
6. 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 MATH 141 Precalculus or an equivalent course. MATH 138 (NS) is a pre-requisite for MATH 141.
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General Education Requirements
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Total Credits
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College Composition I** & II (CCII)
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10 Credits
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Quantitative/Symbolic Reasoning (QSR)
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5 Credits
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Humanities (HU)
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10 Credits
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Social Sciences (SS)
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15 Credits
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Natural Sciences (NS)
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15 Credits
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** If College Composition I is waived through transfer or articulation, students must take an additional 5 quarter credits from a humanities discipline.
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)
| CS 330 | Network Communications | 5 |
| CS 340 | Operating Systems * | 5 |
| CS 351 | Discrete Mathematics in Computing (NS) | 5 |
| IS 302 | Human Computer Interaction | 5 |
| Web Design and Programming | 5 |
| IS 345 | Cybersecurity | 5 |
| IS 350 | Systems Analysis and Design | 5 |
| IS 360 | Database Technologies | 5 |
| IS 471 | Cyber Ethics (SS) | 5 |
Depth of Study: Data Science (30 Credits)
Select 30 credits from the courses listed below.
| CS 469 | Data Structures and Algorithms in Computing | 5 |
| CS 475 | Artificial Intelligence | 5 |
| DS 410 | Programming in Data Analytics * | 5 |
| DS 476 | Data Analysis and Presentation * | 5 |
| DS 479 | Data Mining and Machine Learning * | 5 |
| DS 483 | Mathematics and Statistics for Machine Learning (NS) | 5 |
| DS 484 | Big Data Systems | 5 |
Electives (10 credits)
Students may select two electives from any other undergraduate Depth of Study courses within the School of Technology & Computing or complete the internship after taking three CS 450 seminar courses for their internship preparation.
Seminar
Students can take three CS 450 seminar courses after taking 15 credit hours for core requirements and before taking either CS 493 Technology and Computing Internship 3 or CS 497 Technology and Computing Capstone. Each enrollment must be preapproved by the Program Manager.
| CS 450A | Bachelor's Seminar I in Special Technology * | 2 |
| CS 450B | Bachelor's Seminar II in Special Technology * | 2 |
| CS 450C | Bachelor's Seminar III in Special Technology * | 1 |
Internship
This course is repeatable for credit. Each enrollment must be pre-approved by the Program Manager.
| CS 493 | Technology and Computing Internship * | 5 |
Capstone (5 Credits)
| CS 497 | Technology and Computing Capstone * | 5 |