Undergraduate 2020-2021

CS 422 Directed Studies

A plan should be submitted and approved by all computer science faculty. Individualized investigation under the direct supervision of a faculty member. (Minimum of 37.5 clock hours required per credit hour.)
1- 4

Special Notes

Maximum concurrent enrollment is two times.

Course Attribute

Variable Title Course

Repeatable Status

Course may be repeated 1 times

CS 440 Operating Systems

Study operating systems history, concepts/structure and design; process, processor, memory, file system and input/output management; and representative operating systems.

3

Prerequisites

CS 301 with a minimum grade of C

CS 442 Networking

Study data communications; network structure, design and architectures; network services and standardization; and respective networks all in the framework of the OSI model.
3

Prerequisites

CS 301 with a minimum grade of C

CS 454 Data Mining and Knowledge Discovery

This course considers the use of machine learning and data mining algorithms to discover knowledge embedded in datasets. Topics include techniques such as classification, clustering, predictive and statistical modeling.

3

Prerequisites

(MATH 311 or STAT 411 with a minimum grade of C)

CS 456 Neural Networks and Deep Learning

This course examines state-of-the-art AI approaches to deep learning using neural networks. Students will learn to design neural network architectures and training procedures via hands-on assignments and projects.

3

Prerequisites

(MATH 311 with a minimum grade of C or (CS 120 and MATH 221 and MATH 233 with a minimum grade of C))

CS 460 Problem Solving with Supercomputers

Basics of Linux administration and scripting in an HPC environment. Utilizing an HPC cluster to carry out a significant research project.
3

Prerequisites

CS 120 with a minimum grade of B

CS 480 Graphics

Study graphics theory and applications including the description and transformation of world, viewpoint, eye and screen coordinates, two and three dimensional graphics and hidden line algorithms.

3

Prerequisites

CS 301 with a minimum grade of C

CS 489 Project in Data Science

This is a project course in data science and related fields. Interdisciplinary teams will analyze a new data science problem, develop a model, and control for error and overfitting.

2

Prerequisites

STAT 411 with a minimum grade of C

Mutually Exclusive Course

Credit allowed for only one of these courses: CS 489 and STAT 489

CS 497 Senior Project

A significant computer project will be developed and implemented under the guidance of a computer science professor. A project proposal should be submitted and approved by all computer science faculty.
1- 8

Class Restriction

Include Senior

Repeatable Status

Course is repeatable with a maximum of 8 credit hours