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CS 4337: Organization of Programming Languages
3.00 Credits
The University of Texas at Dallas
Principles of design and implementation of contemporary programming languages. Formal description including specification of syntax and semantics of programming languages. Language definition structures including binding, scoping, data types, control structures, parameter passing, abstraction mechanism, and run-time considerations. Design issues of imperative languages, object-oriented languages, functional languages and logic languages. Design, implement, and debug programs in various programming language paradigms. Prerequisites: CE/CS 2336 or CS 3333, and CE/TE 3307 or CS 2305. (Same as CE 4337) (3-0) S
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CS 4341: Digital Logic and Computer Design
3.00 Credits
The University of Texas at Dallas
Boolean algebra and logic circuits; synchronous sequential circuits; gate level design of ALSU, registers, and memory unit; register transfer operations; design of data path and control unit for a small computer; Input-Output interface. Students who have already completed CS/SE 4340 cannot receive credit for this course. Students cannot get credit for both CS 4341 and CE/EE 3320. Prerequisites: EE 2310 or CS 3340 and PHYS 2326. Corequisite: CS 4141. (3-0) S
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CS 4347: Database Systems
3.00 Credits
The University of Texas at Dallas
This course emphasizes the concepts and structures necessary for the design and implementation of database management systems. Topics include data models, data normalization, data description languages, query facilities, file organization, index organization, file security, data integrity, and reliability. Prerequisite: CS/SE 3345. (Same as SE 4347) (3-0) Y
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CS 4348: Operating Systems Concepts
3.00 Credits
The University of Texas at Dallas
An introduction to fundamental concepts in operating systems: their design, implementation, and usage. Topics include process management, main memory management, virtual memory, I/O and device drivers, file systems, secondary storage management, and an introduction to critical sections and deadlocks. Prerequisites: CS/SE 3340 or CS/SE 4340 or CE/EE 4304, CS/SE 3345 or CE/TE 4346, and a working knowledge of C and UNIX. (Same as CS/SE/TE 4348) (3-0) S
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CS 4349: Advanced Algorithm Design and Analysis
3.00 Credits
The University of Texas at Dallas
Asymptomatic analysis, recurrences, and graph algorithms. Algorithm design techniques such as greedy method, dynamic programming, and divide-and-conquer. Issues from computational complexity. Course emphasizes a theoretical approach. Prerequisite: CS/SE 3345. (3-0) S
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CS 4352: Human Computer Interactions I
3.00 Credits
The University of Texas at Dallas
Methods and principles of human-computer interaction (HCI), user-centered design (UCD), and usability evaluation. Provides broad overview of HCI and how HCI informs UCD processes throughout product development lifecycle. (Same as CGS 4352) (3-0) T
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CS 4353: Human Computer Interactions II
3.00 Credits
The University of Texas at Dallas
Detailed exploration of human-computer interaction (HCI) through readings in journal articles and research reports. Practical experience in methodology typically used in the design of usable systems. Prerequisite: CS 4352 or consent of the instructor. (Same as CGS 4353) (3-0) T
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CS 4361: Computer Graphics
3.00 Credits
The University of Texas at Dallas
Review of graphic display architecture and graphic input devices. Two- and three-dimensional transformations, matrix formulations, and concatenation. Clipping and windowing. Data structures for graphics systems, segmented display files, rings, etc. Hidden line and surface elimination. Shading. Graphics packages and applications. Prerequisites: MATH 2418, CS 2336, and CS/SE 3345. (3-0) Y
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CS 4365: Artificial Intelligence
3.00 Credits
The University of Texas at Dallas
Basic concepts and techniques that enable computers to perform intelligent tasks. Examples are taken from areas such as natural language understanding, computer vision, machine learning, search strategies and control, logic, and theorem proving. Prerequisites: CS 2336 and CS/SE 3345. (3-0) Y
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CS 4375: Introduction to Machine Learning
3.00 Credits
The University of Texas at Dallas
Algorithms for creating computer programs that can improve their performance through learning. Topics include: cross-validation, decision trees, neural nets, statistical tests, Bayesian learning, computational learning theory, instance-based learning, reinforcement learning, bagging, boosting, support vector machines, Hidden Markov Models, clustering, and semi-supervised and unsupervised learning techniques. Prerequisites: CS/SE 3341 and CS/SE 3345. (3-0) Y
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