Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.
MSDS 498-DL : Capstone Project
Description
The capstone course focuses upon the practice of data science.
This course is the culmination of the data science program. It
gives students an opportunity to demonstrate their business
strategic thinking, communication, and consulting skills. Business
cases across various industries and application areas illustrate
strategic advantages of analytics, as well as organizational issues
in implementing systems for data science. Students work in project
teams, generating business plans and project implementation plans.
Students may choose this course or the master's thesis to fulfill
their capstone requirement.
Sections 55, 56, 57: These capstone sections are appropriate for
any student in the MSDS program. Students work on group projects
that reflect learning objectives across the MSDS program: business,
modeling, and information technology.
Section 58: This capstone section is designed for students in
the Analytics & Modeling specialization. While it draws on
learning objectives across the MSDS program (business, modeling,
and information technology), students work individually on projects
with an Analytics & Modeling focus.
Section 59: This capstone section is designed for students
in the Analytics Management specialization. While it draws on
learning objectives across the MSDS program (business, modeling,
and information technology), students work individually on projects
with an Analytics Management focus.
Section 60: This capstone section is designed for students in
the Artificial Intelligence specialization. While it draws on
learning objectives across the MSDS program (business, modeling,
and information technology), students work individually on projects
with an AI focus.
Section 61: This capstone section is designed for students in
the Data Engineering specialization. While it draws on learning
objectives across the MSDS program (business, modeling, and
information technology), students work individually on projects
with a Data Engineering focus.
Prerequisites: Completion of all core courses in the
student's graduate program and specialization.