Catalog Year:

The Data Science Certificate of Achievement provides students with a focused foundation in statistics, programming, and data analysis. This program is designed for individuals seeking to enhance their technical skills for immediate application in the workplace or to build a stepping-stone toward further study in data science and related fields. Students will gain practical experience working with datasets, applying statistical methods, and using modern programming tools to solve real-world problems. This certificate program emphasizes hands-on learning and career-relevant skills. Students will learn to clean, organize, and visualize data, apply statistical techniques, and develop basic predictive and classification models. Coursework integrates the use of widely used programming languages such as Python, R, and/or SQL, preparing students for entry-level roles in data analysis, business intelligence, or related areas. The program is well-suited for those looking to upskill for their current profession, prepare for entry into the data workforce, or lay the groundwork for further academic study 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 data 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