Catalog Year:

The Associate of Science (A.S.) in Data Science provides students with a solid foundation in mathematics, statistics, and programming, preparing them for both immediate entry into the workforce and seamless transfer to a four-year institution. This program equips students with the skills needed to analyze and interpret complex data, apply statistical methods, and build data models using modern programming languages. Whether pursuing a career in data analysis, machine learning, or business intelligence, or continuing education at the bachelor’s level, students will develop the essential technical expertise required for success in the field of data science. This degree program offers a comprehensive curriculum that combines rigorous coursework in mathematics and statistics with hands-on experience in programming and data analysis. Students will learn to clean, visualize, and analyze large datasets, develop predictive and classification models, and use programming languages such as Python, R, and/or SQL to tackle data challenges. The program is designed to provide both practical skills for immediate employment and a strong foundation for advanced studies in data science, computer science, statistics, or related fields.

Career Opportunities

Entry-level positions such as data analyst, data engineer, machine learning engineer, business intelligence analyst, operations Analyst.
Required Courses (22 units)
Units: 22.0
MATH 265A
CALCULUS I
5.0
MATH 265B
CALCULUS II
5.0
CS 231
FUNDAMENTALS OF COMPUTER SCIENCE I
4.0
CS 232
FUNDAMENTALS OF COMPUTER SCIENCE II
2.0
CS 233
FUNDAMENTALS OF COMPUTER SCIENCE III
2.0
MATH 248
FOUNDATIONS OF DATA SCIENCE
4.0
Elective Courses (Select at least 8 units from the following)
Units: 8.0-10.0
MATH 283
CALCULUS III: MULTIVARIABLE CALCULUS
5.0
MATH 287
ORDINARY DIFFERENTIAL EQUATIONS AND LINEAR ALGEBRA
5.0
CS 201
INTRODUCTION TO COMPUTER SCIENCE
3.0
CS 240
MICROCOMPUTER ARCHITECTURE & PROGRAMMING
3.0
CS 241
DISCRETE STRUCTURES
3.0
CS 217
''C'' PROGRAMMING LANGUAGE
3.0
CS 225
CLOUD DATABASES
2.0
ENGR 210
COMPUTATIONAL METHODS FOR ENGINEERS
3.0
PSYC 200
RESEARCH METHODS FOR THE BEHAVIORAL AND SOCIAL SCIENCES
3.0
PHIL 213
PHILOSOPHICAL CLASSICS IN ETHICS AND SOCIAL PHILOSOPHY
3.0
STAT C1000
INTRODUCTION TO STATISTICS
4.0
GEOL 230
INTRODUCTION TO GEOGRAPHIC INFORMATION SYSTEMS
3.0
One of the following
4.0
CIS 210
INTRODUCTION TO COMPUTER APPLICATIONS
4.0
OR
AGB 210
INTRODUCTION TO AGRICULTURAL COMPUTER APPLICATIONS
4.0
Total: 30.0-32.0

Program Outcomes

Outcome
Apply data preprocessing, exploratory analysis, and statistical methods to clean, transform, visualize, and interpret data.
Assessment
Outcome
Apply programming, mathematical foundations, and machine learning techniques to develop models, identify patterns, and generate predictions.
Assessment
Outcome
Assess the limitations and ethical considerations of data science practices and communicate findings using industry-standard tools.
Assessment