Comprehensive Exam Track: Total Credit Hours Required to Finish the Degree ( 36 Credit Hours ) as Follows
Specialization Requirements
Students must pass all of the following courses
|
Course Number |
Course Name |
Weekly Hours |
Cr. Hrs. |
Prerequisite |
||
|---|---|---|---|---|---|---|
|
Theoretical |
Practical |
|||||
| 151036000 | ADVANCED RESEARCH METHODS | The course prepares students for conducting scientific research and development of their thesis work. It aims to promote the nature of science in the students. This course also will guide students as researchers to respect the international standards in the scientific research. It provides content on the logic of inquiry and the necessity for an empirical approach to practice. Furthermore, it addresses the process of formulating appropriate research questions, objectives, and hypotheses, techniques for reviewing literature, approaches for testing relationships and patterns among variables, methods of data collection and analysis, methods for assessing and improving the validity and reliability of data and measurements, and the ethics of scientific research. Some practical experience on various novel topics in Applied Mathematics can be employed for satisfying the mentioned goals. | 3 | - | 3 |
- |
| 151036100 | ADVANCED OPERATING SYSTEMS | The internal and external views of computer operating systems are presented. Fundamentals of systems and system design are stressed. Basic concepts and terminology are emphasized. Advanced concepts of concurrent Processes, communication and synchronization, deadlocks, scheduling, shared resources, resource allocation, and Reallocation, memory management, files management, and protection are discussed. Applications to real systems are investigated to motivate the ideas presented. Students build or run simulations and modify the internals of a working operating system. | 3 | - | 3 |
- |
| 151036120 | ADVANCED NETWORKING | The focus of the course is on the protocols, algorithms and tools needed to support the development and delivery of advanced network services over networks. We will also examine the capabilities provided by emerging ultra-fast network technologies. The course begins with a brief survey of the state of the art in networking technology, examines a collection of new and emerging services and applications, and then examines the algorithms, protocols and software entities involved in delivering new services, wired and wireless networking systems. | 3 | - | 3 |
- |
| 151036150 | ADVANCED ARTIFICIAL INTELLIGENCE | This is a basic graduate level course on Artificial Intelligence (AI). The various topics covered in this course include Semantic Nets, Net Searching Techniques, Heuristic Search, Rule-Based Systems, artificial learning by different methods such as by experience, by correcting mistakes, by training neural nets etc. The students are also introduced to practical AI techniques such as Object Recognition and Edge Detection in image systems and Speech Recognition in language systems etc. | 3 | - | 3 |
- |
| 151036190 | ADVANCED SOFTWARE ENGINEERING | This course provides a comprehensive discussion of software engineering techniques and their application to practical software projects. This course provides coverage of the software process and software process technology, system integration, requirements management, and risk analysis, distributed system engineering, and legacy systems. Java is the choice for all programming examples and all design examples are based on UML notation. The topics covered in this course also include software prototyping, formal specification, software design techniques, critical systems specification and development, software cost estimation and quality management and software re-engineering. | 3 | - | 3 |
- |
| 151036240 | INFORMATION SECURITY | Information security is of vital importance to businesses and administrators and managers must be aware of various security issues in this regard. This course discusses the fundamental concepts of information security, network security practices and system security issues. Topics covered include symmetric and asymmetric cryptography, public-key infrastructure and management, authentication systems, IP security, web security, access control, techniques for identifying vulnerable target systems and types of malicious code, for mitigating security risks, and for recognizing attack patterns. | 3 | - | 3 |
- |
| 151036270 | ADVANCED COMPUTER ARCHITECTURE | General topics in computer architecture, memory systems design and evaluation, pipeline design techniques, RISC architectures, vector computers, VLSI systems architecture. It incorporates the latest research and development on topics such as branch prediction, instruction-level parallelism, multithreading, and cache hierarchy design. | 3 | - | 3 |
- |
| 151036870 | SEMINAR I | An advanced study in a computer sience topic. The student must submit by the end of the course a thesis-style report and present it. | 3 | - | 3 |
- |
| 151036880 | SEMINAR II | A continuation of the study in Seminar I or a new advanced study in a computer sience topic for non-thesis students culminating. The student must submit by the end of the course a thesis-style report and present it. | 3 | - | 3 |
151036870 SEMINAR I An advanced study in a computer sience topic. The student must submit by the end of the course a thesis-style report and present it. |
Students must pass ( 9 ) credit hours from any of the following courses
|
Course Number |
Course Name |
Weekly Hours |
Cr. Hrs. |
Prerequisite |
||
|---|---|---|---|---|---|---|
|
Theoretical |
Practical |
|||||
| 151036180 | DATA MINING | Data Mining studies algorithms and computational paradigms that allow computers to find patterns and regularities in databases, perform prediction and forecasting, and generally improve their performance through interaction with data. It is currently regarded as the key element of a more general process called Knowledge Discovery that deals with extracting useful knowledge from raw data. The knowledge discovery process includes data selection, cleaning, coding, using different statistical, pattern recognition and machine learning techniques, and reporting and visualization of the generated structures. The course will cover all these issues and will illustrate the whole process by examples of practical applications. The students will use recent Data Mining software. | 3 | - | 3 |
- |
| 151036350 | COMPUTER VISION AND PATTERN RECOGNITION | This is an advance course on computer vision and pattern recognition. The topics covered in this course include Segmentation and Classification in images, analysis of Color in Computer Vision, Statistical Pattern Recognition, Syntactic Pattern Recognition and Neural Net Computing for Pattern Recognition etc. This course also discusses the various applications of computer vision and pattern recognition systems in different areas such as Robotics, Speech Recognition and various other industrial applications. | 3 | - | 3 |
- |
| 151036380 | NETWORK MULTIMEDIA TECHNOLOGY | This is an introductory graduate level course on multimedia systems and technologies. It is multi-disciplinary in nature and covers broad areas of Multimedia Information and Entertainment Systems, Digital Signal Processing Technologies for Multimedia, Multimedia File Processing Systems and Multimedia Communication Systems. The topics covered in the Multimedia Information and Entertainment Systems include video conferencing, web-casting/web-seminars, virtual reality systems, MP3 music files, video-on-demand, bandwidth-on-demand and the convergence of computers, communications, and entertainment products. In the Digital Signal Processing Technologies for Multimedia part of the course, the students are introduced to the key concepts of Audio, Image and Video | 3 | - | 3 |
- |
| 151036410 | PERFORMANCE EVALUATION OF COMPUTER NETWORKS | This course studies the methods and concepts of computer and communication network modeling and system performance evaluation. Topics covered include stochastic processes; Queuing theory; Queuing models for media access, error control and traffic management protocols; development of both analytical and simulation models; measurement techniques; monitor tools; work load characterization. Students are required to complete a project. | 3 | - | 3 |
- |
| 151036440 | VALIDATION AND VERIFICATION OF SOFTWARE SYSTEMS | This course covers the terminology and limitation of verification and validation (V and V) approaches. Five approaches will be presented: technical review, testing, proofs of correctness, simulation and prototyping, and requirements tracing. Students will define a V and V plan and carry it out for several stages in the development cycle of a project. | 3 | - | 3 |
- |
| 151036470 | ADVANCED DATABASE MANAGEMENT | This course focuses on advanced databases including active databases, temporal databases, object oriented databases, deductive databases. Its aims is to provide a systematic introduction and an in depth treatment of these advanced database areas. The topics include spatial text and multimedia databases, relational indexing methods, multimedia indexing, advanced transaction models, object database systems. | 3 | - | 3 |
- |
| 151036500 | NEURAL NETWORKS | This course gives an introduction to basic neural network architectures and learning rules. Emphasis is placed on the mathematical analysis of these networks, on methods of training them and on their application to practical engineering problems in such areas as pattern recognition, function approximation and signal processing. | 3 | - | 3 |
- |
| 151036530 | INFORMATION RETRIEVAL | The explosive growth of available digital information (e.g., Web pages, emails, news, scientific literature) demands intelligent information agents that can sift through all available information and find out the most valuable and relevant information. Web search engines, such as Google, Yahoo!, and MSN, are several examples of such tools. This course studies the basic principles and practical algorithms used for information retrieval and text mining. The contents includes: statistical characteristics of text, several important retrieval models, text categorization, recommendation system, clustering, information extraction, etc. The course emphasizes both the above applications and solid modeling techniques (e.g., probabilistic modeling) that can be extended for other applications. | 3 | - | 3 |
- |
| 151036560 | HUMAN COMPUTER INTERACTION | The course will provide a general overview of different goals, principles, user centered development methodologies related to human computer interaction. The objectives of this course are to provide an overview different concepts, problems, theory and evolution of user interfaces in general, to learn more about existing user interfaces and existing techniques and paradigms for user interfaces and to introduce the students to new forms of human-machine interactions. | 3 | - | 3 |
- |
| 151036600 | ADVANCED TOPICS IN COMPUTER SCIENCE | The basic aim of this course is to cover advance topics in Computer Science that are of current interest. Some of the potential topics that can be covered in this course include Net Centric Computing, Distributed Systems Programming, Genetic Algorithms, and Expert Systems etc. | 3 | - | 3 |
- |
Thesis\Treatise Track: Total Credit Hours Required to Finish the Degree ( 36 Credit Hours ) as Follows
Specialization Requirements
Students must pass all of the following courses plus ( 6 ) credit hours for the Thesis
|
Course Number |
Course Name |
Weekly Hours |
Cr. Hrs. |
Prerequisite |
||
|---|---|---|---|---|---|---|
|
Theoretical |
Practical |
|||||
| 151036000 | ADVANCED RESEARCH METHODS | The course prepares students for conducting scientific research and development of their thesis work. It aims to promote the nature of science in the students. This course also will guide students as researchers to respect the international standards in the scientific research. It provides content on the logic of inquiry and the necessity for an empirical approach to practice. Furthermore, it addresses the process of formulating appropriate research questions, objectives, and hypotheses, techniques for reviewing literature, approaches for testing relationships and patterns among variables, methods of data collection and analysis, methods for assessing and improving the validity and reliability of data and measurements, and the ethics of scientific research. Some practical experience on various novel topics in Applied Mathematics can be employed for satisfying the mentioned goals. | 3 | - | 3 |
- |
| 151036100 | ADVANCED OPERATING SYSTEMS | The internal and external views of computer operating systems are presented. Fundamentals of systems and system design are stressed. Basic concepts and terminology are emphasized. Advanced concepts of concurrent Processes, communication and synchronization, deadlocks, scheduling, shared resources, resource allocation, and Reallocation, memory management, files management, and protection are discussed. Applications to real systems are investigated to motivate the ideas presented. Students build or run simulations and modify the internals of a working operating system. | 3 | - | 3 |
- |
| 151036120 | ADVANCED NETWORKING | The focus of the course is on the protocols, algorithms and tools needed to support the development and delivery of advanced network services over networks. We will also examine the capabilities provided by emerging ultra-fast network technologies. The course begins with a brief survey of the state of the art in networking technology, examines a collection of new and emerging services and applications, and then examines the algorithms, protocols and software entities involved in delivering new services, wired and wireless networking systems. | 3 | - | 3 |
- |
| 151036150 | ADVANCED ARTIFICIAL INTELLIGENCE | This is a basic graduate level course on Artificial Intelligence (AI). The various topics covered in this course include Semantic Nets, Net Searching Techniques, Heuristic Search, Rule-Based Systems, artificial learning by different methods such as by experience, by correcting mistakes, by training neural nets etc. The students are also introduced to practical AI techniques such as Object Recognition and Edge Detection in image systems and Speech Recognition in language systems etc. | 3 | - | 3 |
- |
| 151036190 | ADVANCED SOFTWARE ENGINEERING | This course provides a comprehensive discussion of software engineering techniques and their application to practical software projects. This course provides coverage of the software process and software process technology, system integration, requirements management, and risk analysis, distributed system engineering, and legacy systems. Java is the choice for all programming examples and all design examples are based on UML notation. The topics covered in this course also include software prototyping, formal specification, software design techniques, critical systems specification and development, software cost estimation and quality management and software re-engineering. | 3 | - | 3 |
- |
| 151036240 | INFORMATION SECURITY | Information security is of vital importance to businesses and administrators and managers must be aware of various security issues in this regard. This course discusses the fundamental concepts of information security, network security practices and system security issues. Topics covered include symmetric and asymmetric cryptography, public-key infrastructure and management, authentication systems, IP security, web security, access control, techniques for identifying vulnerable target systems and types of malicious code, for mitigating security risks, and for recognizing attack patterns. | 3 | - | 3 |
- |
| 151036270 | ADVANCED COMPUTER ARCHITECTURE | General topics in computer architecture, memory systems design and evaluation, pipeline design techniques, RISC architectures, vector computers, VLSI systems architecture. It incorporates the latest research and development on topics such as branch prediction, instruction-level parallelism, multithreading, and cache hierarchy design. | 3 | - | 3 |
- |
Students must pass ( 9 ) credit hours from any of the following courses
|
Course Number |
Course Name |
Weekly Hours |
Cr. Hrs. |
Prerequisite |
||
|---|---|---|---|---|---|---|
|
Theoretical |
Practical |
|||||
| 151036180 | DATA MINING | Data Mining studies algorithms and computational paradigms that allow computers to find patterns and regularities in databases, perform prediction and forecasting, and generally improve their performance through interaction with data. It is currently regarded as the key element of a more general process called Knowledge Discovery that deals with extracting useful knowledge from raw data. The knowledge discovery process includes data selection, cleaning, coding, using different statistical, pattern recognition and machine learning techniques, and reporting and visualization of the generated structures. The course will cover all these issues and will illustrate the whole process by examples of practical applications. The students will use recent Data Mining software. | 3 | - | 3 |
- |
| 151036350 | COMPUTER VISION AND PATTERN RECOGNITION | This is an advance course on computer vision and pattern recognition. The topics covered in this course include Segmentation and Classification in images, analysis of Color in Computer Vision, Statistical Pattern Recognition, Syntactic Pattern Recognition and Neural Net Computing for Pattern Recognition etc. This course also discusses the various applications of computer vision and pattern recognition systems in different areas such as Robotics, Speech Recognition and various other industrial applications. | 3 | - | 3 |
- |
| 151036380 | NETWORK MULTIMEDIA TECHNOLOGY | This is an introductory graduate level course on multimedia systems and technologies. It is multi-disciplinary in nature and covers broad areas of Multimedia Information and Entertainment Systems, Digital Signal Processing Technologies for Multimedia, Multimedia File Processing Systems and Multimedia Communication Systems. The topics covered in the Multimedia Information and Entertainment Systems include video conferencing, web-casting/web-seminars, virtual reality systems, MP3 music files, video-on-demand, bandwidth-on-demand and the convergence of computers, communications, and entertainment products. In the Digital Signal Processing Technologies for Multimedia part of the course, the students are introduced to the key concepts of Audio, Image and Video | 3 | - | 3 |
- |
| 151036410 | PERFORMANCE EVALUATION OF COMPUTER NETWORKS | This course studies the methods and concepts of computer and communication network modeling and system performance evaluation. Topics covered include stochastic processes; Queuing theory; Queuing models for media access, error control and traffic management protocols; development of both analytical and simulation models; measurement techniques; monitor tools; work load characterization. Students are required to complete a project. | 3 | - | 3 |
- |
| 151036440 | VALIDATION AND VERIFICATION OF SOFTWARE SYSTEMS | This course covers the terminology and limitation of verification and validation (V and V) approaches. Five approaches will be presented: technical review, testing, proofs of correctness, simulation and prototyping, and requirements tracing. Students will define a V and V plan and carry it out for several stages in the development cycle of a project. | 3 | - | 3 |
- |
| 151036470 | ADVANCED DATABASE MANAGEMENT | This course focuses on advanced databases including active databases, temporal databases, object oriented databases, deductive databases. Its aims is to provide a systematic introduction and an in depth treatment of these advanced database areas. The topics include spatial text and multimedia databases, relational indexing methods, multimedia indexing, advanced transaction models, object database systems. | 3 | - | 3 |
- |
| 151036500 | NEURAL NETWORKS | This course gives an introduction to basic neural network architectures and learning rules. Emphasis is placed on the mathematical analysis of these networks, on methods of training them and on their application to practical engineering problems in such areas as pattern recognition, function approximation and signal processing. | 3 | - | 3 |
- |
| 151036530 | INFORMATION RETRIEVAL | The explosive growth of available digital information (e.g., Web pages, emails, news, scientific literature) demands intelligent information agents that can sift through all available information and find out the most valuable and relevant information. Web search engines, such as Google, Yahoo!, and MSN, are several examples of such tools. This course studies the basic principles and practical algorithms used for information retrieval and text mining. The contents includes: statistical characteristics of text, several important retrieval models, text categorization, recommendation system, clustering, information extraction, etc. The course emphasizes both the above applications and solid modeling techniques (e.g., probabilistic modeling) that can be extended for other applications. | 3 | - | 3 |
- |
| 151036560 | HUMAN COMPUTER INTERACTION | The course will provide a general overview of different goals, principles, user centered development methodologies related to human computer interaction. The objectives of this course are to provide an overview different concepts, problems, theory and evolution of user interfaces in general, to learn more about existing user interfaces and existing techniques and paradigms for user interfaces and to introduce the students to new forms of human-machine interactions. | 3 | - | 3 |
- |
| 151036600 | ADVANCED TOPICS IN COMPUTER SCIENCE | The basic aim of this course is to cover advance topics in Computer Science that are of current interest. Some of the potential topics that can be covered in this course include Net Centric Computing, Distributed Systems Programming, Genetic Algorithms, and Expert Systems etc. | 3 | - | 3 |
- |
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