Bachelor of Science, BS
Data Science
The mission of the data science major is to provide the student with the opportunity to study data
science and the intersection of data science with another field with the following student learning
outcomes:
1. Students will demonstrate an understanding of the ethical considerations required
for work in the field of data science,
2. Students will demonstrate the ability to clearly communicate data science
concepts, skills, and outcomes to a variety of audiences at a various levels of
technicality,
3. Students will be able to create readable, documented code to solve data science
issues,
4. Students will demonstrate an understanding of data types, data cleaning, and data
wrangling, and
5. Students will be able to read documentation for data science methods and learn
how to implement new methods to solve problems in different contexts.
Calculation of GPA for Data Science Major or Minor
To earn a degree in data science or complete a minor in data science, a student must have a
minimum GPA of 2.0 in all required coursework.
If the student has more than the minimum required number of elective credits, the credits with
the highest grades will be used in the GPA calculation.
Degrees and Certificates
-
Data Science Major (BS),
Courses
CSC 201: INTRODUCTION TO COMPUTER PROGRAMMING
Class Program
A study of computer systems, program development techniques, and basic programming concepts; emphasis on good programming style; introduction to a high- level programming language. Quantitative GEP requirement.
Prerequisite Courses
Notes
Major, minor, elective credit.
CSC 202: DATA STRUCTURES
Class Program
To continue the study of the fundamental concepts of programming applied to problem solving and to introduce students to the major data structures (arrays, records, stacks, queues, and lists) and their use in Computer Science and classical Computer Science algorithms including searching, sorting, recursion, and pattern matching.
Prerequisite Courses
Notes
Quantitative GEP requirement. Major, minor, elective credit.
CSC 305: DATABASE DESIGN
Class Program
Fundamental principles of database models and database management systems design, implementation, and application. Quantitative GEP requirement.
Prerequisites
CSC 201 or equivalent.
Notes
Minor, Elective credit.
DSC 110: DATA VISUALIZATION
Class Program
This course explores the best methods for data visualization with an emphasis on communicating clearly. Best
practices in visualization type, color, wording, and word placement will be discussed. Real data will be used to
give students real-world experience.
DSC 217: DATA SCIENCE I
Class Program
A study of data and the questions that can be answered by studying data. This course will use both R and Python
to explore algorithms, modeling techniques, and methods of data science.
Formerly MTH 117; changed to DSC 217 in Fall '24.
Prerequisites
Introduction to Programming
Notes
Quantitative GEP credit.
DSC 218: DATA SCIENCE II
Class Program
A continuing study of data and the questions that can be answered by studying data. This course will build on the programming and visualization techniques introduced in Data Science I. Students will encounter more varied data sets and more methods for analyzing data.
Formerly MTH 118; changed to DSC 218 in Fall '24.
Prerequisites
DSC 217 or permission of instructor.
Notes
Quantitative GEP credit.
DSC 300: ETHICS FOR DATA SCIENCE
Class Program
This course explores the ethical considerations surrounding the world of data, data science, data methods, and
data visualization. Various case studies will be explored.
DSC 499: DATA SCIENCE CAPSTONE
Class Program
This course allows students to complete research on a data science topic or project. The student will also present their work and results through a visual presentation and through a professionally written document. Offered every year. Capstone.