Course Descriptions

Course Descriptions

Course Code Course Name Credit
CSE 500 Graduate Seminar (0+1+0) Non-credit
Presentation of topics of interest in computer engineering through seminars given by graduate students, faculty and guest speakers.
CSE 501 Advanced Software Engineering (3+0+0) 3
Study of specific topics in software engineering: program construction and verification, software testing and reliability.
CSE 505 Software Processes (3+0+0) 3
Software process models. Software process assessment and improvement. Personal software process. Software process standards. Software engineering standards. Software quality standards.
CSE 513 Advanced Algorithms (3+0+0) 3
Advanced algorithms for application to computer networks. Intractability and complexity of the algorithms. Graph theory problems and characterization of the problems. Design approaches to optimization algorithms and heuristics.
CSE 514 Programming Languages Syntax and Semantic (3+0+0) 3
Syntax and semantics of imperative, functional and logic languages. Definition of abstract machines for each paradigm. Inheritance in object-oriented languages. Abstract interpretation based on detonational and operational semantics. Compiler design for functional, logic and object-oriented programming language.
CSE 520 Advanced Database Systems (3+0+0) 3
Fundamental concepts of data modeling and popular data models. Design theory for relational databases. Query optimization and data manipulation languages. Concurrency and protection.
CSE 529 Data Mining (3+0+0) 3
Overview of data mining classification; regression, time series. Measuring predictive performance. Data preparation, data reduction. Mathematical solutions, statistical methods, distance solutions, decision trees, decision rules. Text mining. Case studies.
CSE 531 Advanced Operating Systems (3+0+0) 3
Introduction and basic concepts in parallel and distributed operating systems. Synchronization mechanisms. Deadlocks. Inter process communication. Theoretical foundations of distributed operating systems. Task scheduling for multiprocessor and distributed operating systems.
CSE 537 Advanced Network Programming (3+0+0) 3
Overview of network layers. Network programming issues. Socket programming. RPC programming. TLI programming. Web programming. CGI, PERL, PHP and Java programming. Programming projects.
CSE 538 Computer Network Analysis and Design (3+0+0) 3
Introduction to computer network analysis and design. Modeling of traffic flows. Delay and loss models for computer networks. Networks of queues. Measurement and simulation of computer networks. Network design and optimization algorithms. Static and dynamic routing algorithms. Network reliability analysis in design. Wireless network design.
CSE 546 Advanced Computer Architectures (3+0+0) 3
Non Von Neumann machines. High level language machines. Direct execution architecture. Data flow machines. Reconfigurable systems. Super computers. VLSI impact on computer architecture.
CSE 547 Fault Tolerant Computing (3+0+0) 3
Fault modeling. Testing of microprocessor based systems and design for testability. Redundancy techniques to achieve fault-tolerance. Reliability modeling and analysis. Software testing strategies. Software reliability achievement.
CSE 550 Advanced Computer Graphics (3+0+0) 3
Overview of graphics systems. Image models, sampling, and quantization. Image acquisition hardware, stereo imaging and 3D model formation. Modeling techniques for curves, surfaces, and solids. Rendering techniques: ray tracing, volume rendering, procedural texture, radiosity. Light and illumination models. Texture and environment mapping.
CSE 560 Advanced Artificial Intelligence (3+0+0) 3
General problem solving methods in artificial intelligence. Search methods. Production systems. Games and heuristics. Knowledge representation. Artificial intelligence languages.
CSE 562 Pattern Recognition (3+0+0) 3
Bayes decision theory. Parametric and nonparametric methods. Linear discriminant functions. Higher order discriminants with emphasis on artificial neural network-based learning methods. Unsupervised learning and clustering. Case study: vision.
CSE 563 Computer Vision (Bilgisayarla Görme) (3+0+0) 3
Image formation. Early processing: low-level vision and feature extraction. Boundary detection. Region growing. Texture. Motion. Two-dimensional and three-dimensional representation. High-level vision: learning and matching.
CSE 565 Artificial Neural Networks (3+0+0) 3
Introduction to cognitive science. Parallel, distributed problems. Constraint satisfaction. Hopfield model. Supervised and unsupervised learning. Single and multi-layer perceptrons. Static and dynamic network architecture. Comparison of neural approaches with parametric and nonparametric statistical methods. Neural network applications.
CSE 566 Machine Learning (3+0+0) 3
Paradigms and issues of machine learning. Theory and methodology of induction. Instance-based learning. Genetic algorithms, genetic-based machine learning, classifier systems. Learning decision trees. Explanation-based learning. Discovery systems. Learning problem solving strategies.
CSE 567 Image Processing (3+0+0) 3
Mathematical model of an image. Frequency spectrum of an image. Sampling of an image, aliasing and conditions on sampling frequency. Separability in 2-D signals. Periodicity concept in an image. Expansion of an image into Fourier series. Construction of an image from its harmonics. The 2-D Fourier transform. The Fourier transform of separable images. The z-transform and transfer function. The linear operations applied to an image: convolution, mask and impulse response. 2-D FIR filters and IIR filters. Methods of image enhancement. Image segmentation. Image restoration and compression. Cellular neural networks and their applications in 2-D filtering. Recognition and interpretation.
CSE 572 Cryptography (3+0+0) 3
Introduction to cryptography, classical ciphers, block ciphers, DES, AES, modes of operation, stream ciphers, PRNG, LFSR, randomness tests, public key cryptography, RSA, DH, digital signatures, authentication protocols, key exchange, hash functions, elliptic curves.
CSE 580 Term Project Non-credit
In depth study of a computer science or computer engineering topic by M.S. students in the non-thesis option under the guidance of a faculty member.
CSE 581-589 Special Topics in Computer Engineering I-IX (3+0+0) 3
Study of special topics chosen among the recent technological or theoretical developments in computer engineering.
CSE 590 M.S. Thesis Non-credit
Preparation of a M.S. thesis by students of the M.S. program with thesis option under the guidance of an academic advisor.
CSE 640 Advanced Topics in Parallel and Distributed Computing (3+0+0) 3
Parallel methods for computations in the areas of bioinformatics, computational physics, and other disciplines. Parallel algorithms. Topics in distributed computing. Parallel and distributed computing architectures.
CSE 645 Computer Performance Evaluation (3+0+0) 3
Introduction to computer performance measurement and evaluation. Job processing models. Queuing Theory. Simulation techniques. Systems analysis techniques. Estimating CPU performance. Programmed measurement techniques.
CSE 661 Advanced Natural Language Processing (3+0+0) 3
Levels of natural language processing: morphological, syntactic and semantic analysis. Transformational grammars. Affix grammars and 2-level representation and processing. Meaning and interpretation. Applications: intelligent interfaces, text processing aids, machine translation, natural language understanding. Transition networks and ATN parsing.
CSE 664 Computer Speech Processing (3+0+0) 3
Man-machine communication. Speech models and representations. Speech synthesis. Speech coding. Speech recognition. Dynamic time warping and hidden Markow models. Neural networks for speech processing. Speech enhancement.
CSE 681-689 Special Studies in Computer Engineering (3+0+0) 3
Study of current research topics in computer engineering by Ph.D. students under the guidance of a faculty member and presentation of the chosen topic.

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