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UT Dallas CS 1325 - NEU MS CS

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CS 5100. Foundations of Artificial Intelligence. 4 Hours.Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Topicsinclude heuristic search and game trees, knowledge representation using predicate calculus, automateddeduction and its applications, problem solving and planning, and introduction to machine learning.Required course work includes the creation of working programs that solve problems, reason logically,and/or improve their own performance using techniques presented in the course. Requires experience inJava programming.CS 5150. Game Artificial Intelligence. 4 Hours.Offers an overview of classical and modern approaches to artificial intelligence in digital games. Focuseson the creation of believable agents and environments with the goal of providing a fun and engagingexperience to a player. Covers player modeling, procedural content generation, behavior trees,interactive narrative, decision-making systems, cognitive modeling, and path planning. Explores differentapproaches for behavior generation, including learning and rule-based systems. Requires students tocomplete several individual assignments in these areas to apply the concepts covered in class. Studentschoose a group final project, which requires a report, to explore one aspect of artificial intelligence forgames in further depth. Offers students an opportunity to learn team management and communication.Requires knowledge of algorithms and experience with object-oriented design or functionalprogramming.CS 5180. Reinforcement Learning and Sequential Decision Making. 4 Hours.Introduces reinforcement learning and the underlying computational frameworks and the Markovdecision process framework. Covers a variety of reinforcement learning algorithms, including model-based, model-free, value function, policy gradient, actor-critic, and Monte Carlo methods. Examinescommonly used representations including deep learning representations and approaches to partiallyobservable problems. Students are expected to have a working knowledge of probability and linearalgebra, to complete programming assignments, and to complete a course project that applies someform of reinforcement learning to a problem of interest.CS 5200. Database Management Systems. 4 Hours.Introduces relational database management systems as a class of software systems. Prepares students tobe sophisticated users of database management systems. Covers design theory, query language, andperformance/tuning issues. Topics include relational algebra, SQL, stored procedures, user-definedfunctions, cursors, embedded SQL programs, client-server interfaces, entity-relationship diagrams,normalization, B-trees, concurrency, transactions, database security, constraints, object-relationalDBMSs, and specialized engines such as spatial, text, XML conversion, and time series. Includes exercisesusing a commercial relational or object-relational database management system.CS 5310. Computer Graphics. 4 Hours.Introduces the fundamentals of two-dimensional and three-dimensional computer graphics, with anemphasis on approaches for obtaining realistic images. Covers two-dimensional algorithms for drawinglines and curves, anti-aliasing, filling, and clipping. Studies rendering of three-dimensional scenescomposed of spheres, polygons, quadric surfaces, and bi-cubic surfaces using ray-tracing and radiosity.Includes techniques for adding texture to surfaces using texture and bump maps, noise, and turbulence.Requires knowledge of linear algebra.CS 5320. Digital Image Processing. 4 Hours.Studies the fundamental concepts of digital image processing including digitization and display ofimages, manipulation of images to enhance or restore image detail, encoding (compression) of images,detection of edges and other object features in images, and the formation of computed tomography (CT)images. Introduces mathematical tools such as linear systems theory and Fourier analysis and uses themto motivate and explain these image processing techniques. Requires knowledge of linear algebra.CS 5330. Pattern Recognition and Computer Vision. 4 Hours.Introduces fundamental techniques for low-level and high-level computer vision. Examines imageformation, early processing, boundary detection, image segmentation, texture analysis, shape fromshading, photometric stereo, motion analysis via optic flow, object modeling, shape description, andobject recognition (classification). Discusses models of human vision (gestalt effects, texture perception,subjective contours, visual illusions, apparent motion, mental rotations, and cyclopean vision). Requiresknowledge of linear algebra.CS 5335. Robotic Science and Systems. 4 Hours.Introduces autonomous mobile robots with a focus on algorithms and software development, includingclosed-loop control, robot software architecture, wheeled locomotion and navigation, tactile and basicvisual sensing, obstacle detection and avoidance, and grasping and manipulation of objects. Offersstudents an opportunity to progressively construct mobile robots from a predesigned electromechanicalkit. The robots are controlled wirelessly by software of the students’ own design, built within a providedrobotics software framework. Culminates in a project that connects the algorithms and hardwaredeveloped in the course with a selected topic in the current robotics research literature.CS 5340. Computer/Human Interaction. 4 Hours.Covers the principles of human-computer interaction and the design and evaluation of user interfaces.Topics include an overview of human information processing subsystems (perception, memory,attention, and problem solving); how the properties of these systems affect the design of user interfaces;the principles, guidelines, and specification languages for designing good user interfaces, with emphasison tool kits and libraries of standard graphical user interface objects; and a variety of interfaceevaluation methodologies that can be used to measure the usability of software. Other topics mayinclude World Wide Web design principles and tools, computer-supported cooperative work, multimodaland “next generation” interfaces, speech


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UT Dallas CS 1325 - NEU MS CS

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