Graduate Programs

Data Science Graduate Certificate

Virtual Open House

Thursday, November 2: 5-6:30pm

Join us at one of our upcoming virtual Graduate School Open House events on Zoom! You'll have the opportunity to learn more about Western Carolina University,  understand the Graduate School application process, and meet key program representatives.

Register Today

The Graduate Certificate in Data Science is designed for the part-time student who wants to improve their skills in managing, visualizing and modeling with data.

Admissions requirements: A Bachelor’s degree in mathematics or a business, science or technology field with previous coursework in Calculus I-II, computer science or programming experience, and introductory statistics. The GRE is not required for admission.

The certificate is earned through the completion of four three-credit courses, one per fall and spring semester and a one-credit capstone course in their final spring semester.

A student who successfully completes the certificate will be able to: 

• Synthesize modes of thought in statistics, computer science and mathematics
• Understand both the computational and modeling challenges in a task, and how they might be intertwined
• Investigate models using data visualization to communicate with others and identify weaknesses in proposed models
• Build and assess statistical and machine learning models and draw conclusions of appropriate scope from the analysis
• Apply algorithmic problem-solving skills and implement solutions through programming in a suitable high-level language
• Manage data through the entire problem-solving process
• Communicate the results from a statistical analysis orally and in writing in an appropriate level of detail for an intended audience

Courses will be offered at both the WCU main campus in Cullowhee and at the WCU Biltmore Park instructional site, with a hybrid of face-to-face and online instruction. 

Degree requirements (13 semester credit hours) 

Core

MATH 572 Data Science (3)
MATH 574 Introduction to Statistical Models (3)
MATH 575 Statistical Machine Learning (3)
MATH 678 Data Science Capstone (1)

Electives (choose one)

MATH 530 Mathematical Modeling (3)
MATH 541 Introduction to Numerical Analysis (3)
MATH 550 Linear Optimization (3)
MATH 562 Linear Algebra II (3)
MATH 570 Probability and Statistics II (3)
MATH 571 Problem Solving for Exam P (3)
CS 580 Artificial Intelligence (3)

Math course projections