Bachelor of Science in Data Science

Enrollment

All Quarters

Course Format

Online, Mixed Mode, On-Site (Seattle)

Total Credits

180

Help Organizations Make Data-Driven Decisions

The Bachelor of Science in Data Science (BSDS) is specifically designed for students seeking to enter an emerging field of data science. The BSDS provides graduates with the skills, knowledge, and abilities to understand and process data and extract valuable information to assist in making data-driven decisions for organizations. As our world becomes more digitized and filled with data, Harvard Business Review reported the data scientist is the sexiest job of the 21st century.

The BSDS program offers flexible learning options, both mixed–mode and online. The bachelor’s program follows the Body of Knowledge of the Association for Computing Machinery (ACM) Data Science and aligns with ABET standards.

Program Overview

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.

Learning 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).

Lower Division Requirements

Total Required Credits: 90

Students must meet General Education requirements.  This is typically completed within the 90 required lower division credits. See the General Education Requirements section in the catalog for more detailed information.

For this program, Quantitative/Symbolic Reasoning is met with  MATH 141 Precalculus or higher.  MATH 138 (NS) is a pre-requisite for MATH 141.

General Education Requirement (55 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 (15 Credits)

CS 132 Computer Science I *
CS 251 Statistical Computing (NS) *  
IS 201 Fundamentals of Computing I

Requirements

Total Required Credits: 90

Core Requirements (45 Credits)

CS 320 Fundamentals of AI *
CS 330 Network Communications *
CS 340 Operating System and Administration*
CS 351 Discrete Mathematics in Computing (NS) *
IS 312 Web Design and Programming *
IS 345 Cybersecurity
IS 360 Database Technologies
IS 471 Cyber Ethics (SS)
IT 434 Cloud Computing *

Depth Study: Data Science (30 Credits)

Select 30 credits from the courses listed below.

CS 469 Data Structures and Algorithms in Computing *
CS 475 Artificial Intelligence
DS 410 Programming in Data Analytics *
DS 476 Data Analysis and Presentation *
DS 479 Data Mining and Machine Learning *
DS 483 Mathematics and Statistics for Machine Learning *
DS 484 Big Data Systems *
IS 465 Database Systems Management *

Electives (10 Credits)

Students may select two electives from any other undergraduate upper-division courses within the School of Technology & Computing or complete the internship.

Internship
This course is repeatable for credit. Each enrollment must be pre-approved by the Program Manager.

CS 493 Technology and Computing Internship *

Capstone (5 Credits)

CS 497 Technology and Computing Capstone *

Career Opportunities

Undergraduate Program Director

Michael Lahman
lahmanmichael@cityu.edu

With the global Big Data & analytics market already worth over $348 billion and employment of data scientists projected to grow 36 % between 2023 and 2033, the need for professionals who can translate data into insight keeps accelerating. Data science isn’t just about reporting the past – it’s about predicting and optimizing the future.

Graduates of CityU’s Bachelor of Science in Data Science (BSDS) exit the program ready for entry-level and early-career roles such as:

Data Analyst / Junior Data Scientist: Explore, clean, and model data using Python, SQL, and tools like pandas and scikit-learn; communicate insights through visualizations and executive dashboards.
Analytics Engineer / BI Developer: Build analysis-ready data models, create dashboards, and support decision-making with real-time analytics powered by tools like Power BI and Tableau.
Data Engineer: Develop pipelines that feed machine learning systems, manage structured/unstructured data, and implement ETL workflows using cloud services and open-source tools.
Machine Learning Associate: Assist in building, testing, and deploying supervised and unsupervised models using platforms like AWS SageMaker or Azure ML -supporting projects in NLP, forecasting, and classification.
AI & Data Product Associate: Support the development of data-driven and AI-powered products, helping define user needs, KPIs, and success criteria from prototyping to launch.
Data Quality & Ethics Analyst: Monitor data integrity, privacy, and fairness—ensuring ethical use of AI and compliance with data regulations (e.g., GDPR, CCPA).

CityU’s BSDS graduates work with teams at Adobe, AWS, Google, and Microsoft, among others, helping to power intelligent systems and insights in areas such as:

Retail & e-Commerce – recommendation systems, demand forecasting
Healthcare – predictive diagnostics, AI-supported triage
Finance & Insurance – fraud detection, credit scoring, robo-advisors
Manufacturing & IoT – sensor analytics, predictive maintenance
Energy & Environment – smart-grid analytics, sustainability modeling
Civic Tech & Public Sector – AI for policy modeling, service optimization

Click HERE for admissions and tuition information.

Click HERE for the complete program catalog.

Updated: 7/30/2025

School of Technology and computing