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For students entering in 2023-24

» Data Science (B.S.): Suggested 4-year Plan for 2023-24

How to Use your 4-year Plan

This is a suggested 4-year plan for your major and not meant to replace regular academic advising.
The plan is flexible and can be changed to accommodate studying abroad, a second major/minor(s) or AP/IB credits.
You should work with an academic advisor to develop a plan that meets your interests and goals.
You must earn a minimum of 120 credits to graduate and 75 major-specific credits to earn a B.S. in Data Science.
Transfer students and those seeking second majors should contact the program advisor for degree planning.
If you have any questions, contact fseadvising@chapman.edu.

Suggested 4-year Plan

We encourage you to select your General Education (GE) and minor/second major/Themed Inquiry/Honors program around the plan below. Once you fill your GE classes around your major classes, you will have a better idea of space remaining each semester when choosing your Exploration Focus.
To be enrolled full time, you must take at least 12 credits a semester.
In order to graduate within 4 years, we recommend you take 30 credits a year.

Year 1

Fall Semester (13 credits for major)

FFC100B - Grand Challenges in Science and Engineering (3 credits)
ENGR101 - Introduction to Design and Fabrication (3 credits)
CPSC230 - Computer Science I (3 credits)
CPSC298 - Intro to *Nix (1 credit)
MATH110 - Single Variable Calculus I (3 credits)

Spring Semester (8 credits for major)

CPSC231 - Computer Science II (3 credits)
CPSC298 - Computer Science Colloquium, any topic (1 credit)
SCI150 - Grand Challenges in Science and Engineering I (1 credit)
MATH203 - Intro to Statistics (3 credits)

Year 2

Fall Semester (8 credits for major)

ECON200 - Principles of Microeconomics (3 credits)
CPSC298 - C++ Programming (1 credit)
MGSC220 - Foundation of Business Analytics (3 credits)
SCI200 - Grand Challenges in Science and Engineering II (1 credit)

Spring Semester (10 credits for major)

Data Science Upper Division Requirement (3 credits)
Data Science Upper Division Requirement (3 credits)
CPSC293 - Mathematical Foundations for Machine Learning (3 credits)
SCI250 - Grand Challenges in Science and Engineering III (1 credit)

Year 3

Fall Semester (10 credits for major)

CPSC298 - Computer Science Colloquium, any topic (1 credit)
Data Science Upper Division Requirement (3 credits)
Data Science Elective (3 credits)
CPSC285 - Social Issues in Computing (3 credits)

Spring Semester (10 credits for major)

Data Science Upper Division Requirement (3 credits)
Data Science Upper Division Requirement (3 credits)
Data Science Upper Division Requirement (3 credits)
CPSC298 - Computer Science Colloquium, any topic (1 credit)

Year 4

Fall Semester (9 credits for major)

Data Science Upper Division Requirement (3 credits)
Data Science Upper Division Requirement (3 credits)
Data Science Elective (3 credits)

Spring Semester (10 credits for major)

CPSC298 - Computer Science Colloquium, any topic (1 credit)
Data Science Upper Division Requirement (3 credits)
Data Science Upper Division Requirement (3 credits)
Data Science Science Elective (3 credits)