Data Science Minor

Requirements for a Minor in Data Science

A minor in Data Science requires a minimum of six courses and a capstone project. One of the following six courses may be taken credit / no credit. The minor has the following requirements:

A Computer Programming course^a (CSCI 051A PO , CSCI 051P PO , CSCI 005 HM , CSCI040 CM, CSCI004 PZ, MS 059 SC)
Introduction to Statistics^b (MATH 058 PO , MATH 058B PO , ECON 057 PO , LGCS 123 PO , PSYC 158 PO )
Foundations of Data Science (DS 002R PO , DS 002 SC, CSCI036 CM, CSCI036 PZ)
Ethics & Justice (ANTH 015 PO , DS 108 PZ, PHIL 002 PO , PHIL 032 PO , PHIL034 CM, PHIL 035 PO , PHIL 036 PO , PHIL 057 JT , PHIL 125 HM , PHIL158 CM, PHIL198 SC, PPE 100 PO , PSYC 183 SC )
Linear Algebra (MATH 060 PO )
A minimum of one additional upper division course (involving data, data ethics, data driven decision making) selected in consultation with a Data Science minor advisor.
To fulfill the Data Science minor, either the student’s Introduction to Statistics or upper division course must have a substantial component of coding/programming with data or coding/programming algorithms. For example, if your introductory statistics course uses a software program with pull-down menus instead of scripting, your upper division course should use scripting. The list of pre-approved upper division electives with programming are provided below.
Capstone in Data Science (DS 190 PO )

Capstone project (one semester, 0.5 credits, data analysis beyond course work, in an applied discipline other than statistics, mathematics, or computer science)^c. Each student will carry out and communicate results from an extensive data-driven project from a discipline outside of statistics, mathematics, and computer science. To structure the project, the student will enroll in a Data Science Capstone course.

Each student will take a 0.5 credit capstone project class in the fall of their senior year.
Students must complete all of the five core data science requirements prior to the capstone project class.
The capstone must be new to the student, i.e., it may not be a previous project, as is or with minor extensions, from a previous class or summer experience. However, the capstone could be a substantial extension of a previous project (outside of statistics, mathematics, and computer science). The capstone must comply with the College’s policy on duplication of coursework .
The method(s) applied to the data should go beyond the topics covered in the core data science minor courses.
To ensure a smooth transition into the capstone, students will be required to submit their disciplinary interest to their prospective affiliated advisor in the spring of their junior year to the Data Science steering committee, with the confirmation from the student’s affiliated faculty member.

_{a. Only CSCI051P PO counts for the Pomona Computer Science major. Students with plans to pursue Computer Science should not take introductory computer science courses elsewhere.

b. A student who has taken Introduction to Statistics prior to matriculation can fulfill the statistics requirement through an upper division statistics course; a student who has taken introductory Computer Science can fill the Computer Science requirement through an upper division Computer Science course.

c. Note that the capstone project requires that students have taken courses outside of statistics, computer science, and mathematics. The capstone sould build on courses in the student’s applied discipline.}