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 (70 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.
|
General Education Requirements
|
Total Credits
|
|
College Composition I** & II (CCII)
|
10 Credits
|
|
Quantitative/Symbolic Reasoning (QSR)
|
5 Credits
|
|
Humanities (HU)
|
10 Credits
|
|
Social Sciences (SS)
|
15 Credits
|
|
Natural Sciences (NS)
|
15 Credits
|
** If College Composition I is waived through transfer or articulation, students must take an additional 5 quarter credits from a humanities discipline.
Preparatory Courses (20 Credits)
These preparatory courses may be applied towards CityU's General Education and Lower Division credit requirements.
| MATH 138 | College Algebra (QSR or NS) | 5 |
| CS 132 | Computer Science I | 5 |
| CS 251 | Statistical Computing (QSR for select programs OR NS) | 5 |
| IS 201 | Fundamentals of Computing | 5 |
Data Science Major (45 Credits)
| CS 330 | Network Communications | 5 |
| CS 340 | Operating Systems * | 5 |
| CS 351 | Discrete Mathematics in Computing (NS) | 5 |
| CS 320 | Fundamentals of Artificial Intelligence * | 5 |
| IS 312 | Web Design and Programming * | 5 |
| IS 345 | Cybersecurity | 5 |
| IT 434 | Cloud Computing | 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 |
| IS 456 | Database Systems Management * | 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 elective courses from any upper-division courses within STC.
Capstone (5 Credits)
| CS 497 | Technology and Computing Capstone * | 5 |