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    For students entering in 2023-24
Data Science (B.S.) Suggested 4-year Plan

Academic Advising

» 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)

Chapman Catalog

Data Science (B.S.)


View all requirements, courses, and electives and elective groups on the Data Science (B.S.) catalog page.