Graduate Courses

CS 521 Artificial Intelligence

Applications of artificial intelligence including advanced topics. Topics include: inference, knowledge representation, search, cognitive architecture, decision making under uncertainty, and machine learning. Special project required. Knowledge of data structures required.

3

Cross Listed Courses

CS 421

CS 523 Computational Biology

Study of advanced algorithmic and analysis techniques for biological data such as DNA, RNA, proteins and gene expression. Topics and project include molecular biology, alignment and searching algorithms, sequence evolution algorithms, genetic trees and analysis of microarray data. Interdisciplinary course that assumes programming skills. Special project required. Knowledge of data structures, biology, and programming required.

3

Cross Listed Courses

CS 423, BIO 423

CS 525 Introduction to Robotics

Concepts in robotics including state estimation, filtering, perception, localization, and mapping. Introduction to various topics in computer vision. Methods for robotic control and learning. Current topics in applied robotics. Special project required. Knowledge of statistics, calculus, and data structures required.

3

Prerequisites

Graduate standing.

Cross Listed Courses

CS 425

CS 527 Internet of Things

This is a practical course in "Making Smart Connected Things". Today, IoT exists in our home appliances, automobiles, airplanes, and on our wrists - tracking how we exercise, and measuring and analyzing our sleep. Topics include core IoT technologies (hardware, software, circuits, sensors) applied to hands-on projects. Special project required. Knowledge of data structures required. Fee: $100

3

Cross Listed Courses

CS 427

CS 528 User Experience Design

Learn about UX (User Experience) Design to gain practical insights into staying focused on the right work for the right people. Go in-depth into areas of user research, information architecture, and information design. Other areas of study will include interaction design, visual design, accessibility, story boarding, and game mechanics. Prior experience in data structures is required.

3

Cross Listed Courses

CS 428

CS 529 Introduction to Machine Learning

In-depth survey of basic and advanced concepts of machine learning. Topics include: linear discrimination, supervised, unsupervised, semi-supervised learning, multilayer perception, convolution neural networks, maximum-margin methods, Monte-Carlo, and reinforcement learning.  Prior knowledge of data structures is required.  Knowledge of linear algebra and vector calculus also recommended.  Research project requiring an application of a machine learning techniques.

3

Cross Listed Courses

CS 429

CS 532 Computer Graphics

An examination of topics in computer graphics, including graphical output devices, line-drawing and clipping algorithms, representation and drawing of curves, techniques for transforming graphical images, and methods of modeling and rendering in three-dimensions. Special project required. Knowledge of data structures, linear algebra, and calculus are required.

3

Cross Listed Courses

CS 432

CS 534 Database Management Systems

The design and implementation of databases with an emphasis on the use of relational database management systems (DBMS). Special project using DBMS. Exploration of query languages, table and index design, query evaluation, transaction management, tuning, security. Special project required. Knowledge of data structures required.
3

Cross Listed Courses

CS 434

CS 536 Parallel Computing

A study of architectures, algorithms and programming/debugging techniques that employ parallelism to increase performance of computer programs. Topics include parallel computer architectures, parallel programming languages for distributed and shared-memory multiprocessors and code optimization. Special project required. Knowledge of data structures, computer architecture, and object oriented design required.

3

Cross Listed Courses

CS 436

CS 538 Introduction to Big Data Analytics

As more data becomes available, solutions are needed to store, process, extract, interpret, and visualize large amounts of data. This course introduces algorithms and technologies for the storage, modeling, analysis, visualization, interpretation, and use of data. Special project required. Knowledge of statistics and data structures required.

3

Cross Listed Courses

CS 438

CS 543 Cloud Computing

Cloud computing is the delivery of on-demand computing resources, from applications to data centers, over the Internet with pay-as-you-go pricing. Study fundamentals and capabilities of cloud across various service models. Topics include cloud infrastructure, programming models, and security and privacy issues in cloud computing. Includes various case studies from industry. Special project required. Knowledge of data structures required.

3

Cross Listed Courses

CS 443

CS 545 Computer Networks and Internetworking

Computer networks and internetworking. Specialized applications of OSI and TCP/IP layered models, TCP/IP protocol suite, transmission media, local area network and transport-layer protocols, internetworking, internet addressing and routing. Special project required. Knowledge of data structures required.

3

Cross Listed Courses

CS 445

CS 547 Computer Game Design

Computer game design emphasizing the philosophy, objectives, and history of this field. In addition, the course will emphasize advanced applications of some of the more prevalent techniques. Special project required. Knowledge of data structures required.

3

Cross Listed Courses

CS 447

CS 548 Topics in Cybersecurity

Cryptography, program security, security in operating systems, security in computer networks, security administration and policies. Special project required. Knowledge of data structures and unix required. Fee: $50

3

Cross Listed Courses

CS 448

CS 590 Directed Study

Credit arranged.

Variable

CS 591 One Time Course Offering

Credit arranged.

Variable

CS 592 One Time Course Offering

Credit arranged.

Variable

CS 593 Research

Faculty-directed student research. Before enrolling, a student must consult with a faculty member to define the project. May be repeated for credit.
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