Content varies annually, depending on instructor interests and the needs of the department. Similar to CS 5501 and CS 7501, but taught strictly at the undergraduate level. Prerequisite: Must have completed CS 2100 with a grade of C- or better. Additional specific requirements vary with topics.

Viruses, worms, and other malicious software are an ever-increasing threat to computer systems. There is an escalating battle between computer security specialists and the designers of malicious software. This course provides an essential understanding of the techniques used by both sides of the computer security battle. Prerequisite: CS 3710 with a grade of C- or better

Introduces artificial intelligence. Covers fundamental concepts and techniques and surveys selected application areas. Core material includes state space search, logic, and resolution theorem proving. Application areas may include expert systems, natural language understanding, planning, machine learning, or machine perception. Provides exposure to AI implementation methods, emphasizing programming in Common LISP. Prerequisite: CS 3100 with a grade of C- or better

Mobile computing devices have become ubiquitous in our communities. In this course, we focus on the creation of mobile solutions for various modern platforms, including major mobile operating systems. Topics include mobile device architecture, programming languages, software engineering, user interface design, and app distribution. Prerequisite: CS 3140 with a grade of C- or better

This course will introduce students to the concepts and tools used in the development of modern 2-D and 3-D real-time interactive computer video games. Topics covered in this include graphics, parallel processing, human-computer interaction, networking, artificial intelligence, and software engineering. Prerequisite: CS 3140 with a grade of C- or better

Investigates the architectural foundations of the various cloud platforms, as well as examining both current cloud computing platforms and modern cloud research. Student assignments utilize the major cloud platforms. Prerequisite: CS 3140 with a grade of C- or better

Introduces the fundamental concepts for design and development of database systems. Emphasizes relational data model and conceptual schema design using ER model, practical issues in commercial database systems, database design using functional dependencies, and other data models. Develops a working relational database for a realistic application. Prerequisite: CS 2120 and 3140 with a grade of C- or better

This course explores Natural Language Processing (NLP), examining how computers are trained to understand and process human language. Students will gain a thorough understanding of both core NLP concepts and advanced techniques, including text analysis, language modeling, machine translation, question answering, text generation, conversation modeling, and the latest advancements in large language models. Prerequisite: CS 3100 with a grade of a C- or better and APMA 3080 or equivalent.

This course aims to give an introduction to basic ideas and concepts of RL while avoiding deep dive in mathematical treatments. The course will help the student build an intuitive understanding of RL and give students hands-on experience on small-scale RL problems. Prerequisite: CS 2100 with a grade of C- or better or successfully complete the CS 2100 place out test.

An introduction to machine learning: the study of algorithms that improve their performance through experience. Covers both machine learning theory and algorithms. Introduces algorithms, theory, and applications related to both supervised and unsupervised learning, including regression, classification, and optimization and major algorithm families for each. Prerequisites: CS 3100 with a grade of C- or better. Background in topics covered in Probability and Linear Algebra is required.