Data Science, BS

The BS Data Science, offered by the Department of Computer Science , prepares students with foundational knowledge and skills for data science careers. It features a computing-based curriculum and instructs students in the theory and practice of data management, machine learning, and computing analysis of data-centered problems. Its balanced coursework provides students with strong analytical, computing, and data-focused skills to understand and solve problems for business and research, with societal, cultural impacts. Graduates of this program will have the necessary knowledge, tools, and skills for solving complex real-world problems, drawing conclusions from data-driven methodologies. Students will meet the qualifications for data scientist positions in industry and government and will apply a sound understanding of the social and ethical implications of data analytics in their work as data scientists.

Program Learning Outcomes

Program Roadmaps

The 4-Year Roadmap is available online. Roadmaps should be used in consultation with the catalog and your advisor to identify additional requirements for completing the major (for example, course grade minimums). Associate Degrees (ADT) Pathways are also available online.

Major-Specific Graduation Requirements

A grade of “C-” or better is required for courses being used to meet any requirement in any minor or major offered by the Department of Computer Science, including Major Preparation courses.

1. Complete the Baccalaureate Degree Requirements

Students must satisfy the specific degree requirements for their undergraduate major and fulfill the following University degree requirements:

Academic (program total units with an average 2.0 GPA - “C” or better)
General Education (GE) (34 Lower Division + 9 Upper Division)
American Institutions (AI) (0-6 units) (may be satisfied in GE Areas 3B, 4, UD 3, UD 4)
Graduation Writing Assessment Requirement (GWAR) (3 units)
Physical Education (PE) (0-2 units)
Units in Residence (30 units, including 24 upper division and 12 in major)
Upper Division Units (40 units, including 12 upper div in major for BA, 18 upper div in major for BS)
Undergraduate Policies & Procedures
Apply for Graduation
Information about the Commencement Ceremony and Conferral of the Degree

Exceptions for University Graduation Requirements including exemptions and waivers, are approved for specific majors and on a case-by-case evaluation only.

Summary of Degree Units

Core Lower Division GE: 25 (3 units may be satisfied by major coursework: Area 2)

6 required units of American Institutions/US123 may be satisfied by selecting applicable GE courses in Areas 3B and/or 4

Upper Division GE: 6 (3 units may be satisfied by major coursework: UD Area 3)

Physical Education: 2

GWAR / WID: 0 (3 units may be satisfied by CS 100W )

Major Preparation: 25

Major Requirements: 56

Total: 120

2. Major Preparation (25 units)

MATH 30 - Calculus I 3 unit(s) (GE Area 2 / Formerly Area B4)
MATH 31 - Calculus II 4 unit(s) (GE Area 2 / Formerly Area B4)
MATH 39 - Linear Algebra I 3 unit(s)
MATH 42 - Discrete Mathematics 3 unit(s)
MATH 161A - Applied Probability and Statistics I 3 unit(s)
MATH 167R - Statistical Programming with R 3 unit(s)
CS 100W - Technical Writing Workshop 3 unit(s) (WID)
PHIL 133 - Ethics in Science 3 unit(s) (GE UD Area 3 / Formerly Area V)

3. Major Requirements (56 units)

CS 22A or CS 122 (3 units)

Complete one course:

CS 22A - Python for Everyone 3 unit(s) (requires prior department approval) (GE Area 2 / Formerly Area B4)
CS 122 - Advanced Programming with Python 3 unit(s)

Lower Division (8 units)

CS 46A - Introduction to Programming 4 unit(s) or CS 46AX - Introduction to Programming 4 unit(s)
CS 46B - Introduction to Data Structures 4 unit(s)

Upper Division (21 units)

CS 131 - Processing Big Data - Tools and Techniques 3 unit(s)
CS 133 - Introduction to Data Visualization 3 unit(s)
CS 146 - Data Structures and Algorithms 3 unit(s)
CS 156 - Introduction to Artificial Intelligence 3 unit(s)
CS 157A - Introduction to Database Management Systems 3 unit(s)
CS 163 - Data Science Senior Project 3 unit(s)
CS 171 - Introduction to Machine Learning 3 unit(s)

Major Electives (15 units)

Complete 15 units from the following courses:

CS 22B - Python Programming for Data Analysis 3 unit(s)
CS 47 - Introduction to Computer Systems 3 unit(s)
CS 48 - Applied Algorithms 1 unit(s)
CS 49J - Programming in Java 3 unit(s) (may be used with prior approval)
CS 85A - Practical Computing Topics 1 unit(s) (may be used with prior approval)
CS 116A - Introduction to Computer Graphics 3 unit(s)
CS 122 - Advanced Programming with Python 3 unit(s)
CS 123A - Bioinformatics I 3 unit(s)
CS 123B - Bioinformatics II 3 unit(s)
CS 136 - Introduction to Computer Vision 3 unit(s)
CS 151 - Object-Oriented Design 3 unit(s)
CS 155 - Introduction to the Design and Analysis of Algorithms 3 unit(s)
CS 157B - Database Management Systems II 3 unit(s)
CS 157C - NoSQL Database Systems 3 unit(s)
CS 158A - Computer Networks 3 unit(s)
CS 166 - Information Security 3 unit(s)
CS 176 - Introduction to Social Network Analysis 3 unit(s)
CS 185C - Advanced Practical Computing Topics 3 unit(s) (At most 6 units may be used)
CS 190 - Internship Project 1 unit(s) or CS 190I - Internship Project 3 unit(s) (At most 3 units may be used)
MATH 32 - Calculus III 3 unit(s)
MATH 161B - Applied Probability and Statistics II 3 unit(s)
MATH 161C - Applied Probability and Statistics III 3 unit(s)
MATH 163 - Probability Theory 3 unit(s)
MATH 164 - Mathematical Statistics 3 unit(s)
SSCI 101 - Leadership and Career Accelerator 3 unit(s)

Domain Field Electives (9 units)

Complete 9 units of major requirement courses of one particular major program (excluding BS - Computer Science, BS - Software Engineering, and BS - Information Science and Data Analytics) to gain domain expertise; requires prior department approval.

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