The Computer Science Major and Minor at Davidson

Computer science combines problem-solving skills with cutting-edge technology to develop automated solutions and systems with diverse applications.

A major or minor in Computer Science supports students interested in core computing ideas and techniques, and in the application and expression of those concepts for the benefit of society. Recent graduates work in industry or pursue graduate degrees in computer science and related fields at programs including Stanford, Duke, and University of Maryland College Park. Students regularly compete in programming competitions and hack-a-thons, collaborate with faculty on research, and publish and present papers at international computer science conferences. Student organizations promoting diversity in computer science include FICSIT and D-Code.

Students interested in declaring a computer science major may ask any continuing faculty member to serve as their major advisor, with whom they will meet to complete the Computer Science Major Declaration Form (PDF).

Students interested in declaring a computer science minor submit the Computer Science Minor Declaration Form (PDF) to the department chair.

Math and Computer Science Course Ceiling Exception Request

Courses You Might Take

CSC 110

Data Science & Society

Instructor
C. Smith

An introduction to methods of data science, including computer programming, data visualization, and statistical analysis. Students will collect, process, analyze, and present data in order to expose and help each other understand issues of social and economic…

CSC 250

Computer Organization

Instructor
Wiedenbeck

An introduction to how digital computers are built and the process by which computer programs expressed in a high-level language are translated into signals to be routed on a digital circuit board. Topics include data representation and manipulation…

CSC 381

Recommender Systems Research

Fall 2020

Deep Learning
Instructor

Wiedenbeck

This course focuses on theoretical foundations and practical applications of deep learning, the subfield of machine learning concerned with large neural networks trained on large data sets. Topics include training models by stochastic gradient descent, implementing various neural…