Pre-Master's Course Description in Information Systems
Pre-Master's Course Description in Information Systems
Compulsory Courses
IS601: Decision Support and Intelligent Systems [3 CH]
The course focuses on the new trends and future prospects of Intelligent Decision Support Systems. Large-scale, stochastic, fuzzy, and using of intelligent tools are some examples of the proposed topics. Real and practical applications and case studies of Operations Research and Decision Support Systems in different fields are recommended, examples of these fields are: computer applications, risk analysis, banking, logistics, military, chemical, oil industry, production, agriculture, airspace, education, naval transport, and others. Recent papers and publications in Operations Research and Decision Support Systems can be used to inform students about recent trends and to train them reading and understanding scientific writing.
IS602: Advanced Database Management Systems [3 CH]
Implementation of database management systems, the impact of new technology on database management systems, back-end database computers, distributed database management systems, concurrency control and query execution in both distributed and centralized systems, implementation of multiple user views, roll-back and recovery mechanisms, database translation.
IS603: Big Data Analytics [3 CH]
The objective of the course is to familiarize students with big data analysis as a tool for addressing substantive research questions. The course begins with a basic introduction to big data and discusses what the analysis of these data entails, as well as associated technical, conceptual and ethical challenges. Strength and limitations of big data research are IScussed in depth using real-world examples. Students then engage in case study exercises in which small groups of students develop and present a big data concept for a specific real-world case. This includes practical exercises to familiarize students with the format of big data. It also provides a first hands-on experience in handling and analyzing large, complex data structures. The block course is designed as a primer for anyone interested in attaining a basic understanding of what big data analysis entails. There are no prerequisite requirements for this course.
IS604: Information Systems Security [3 CH]
Overview of computer security. Access control matrix Security policies Confidentiality policies Integrity policies Hybrid policies Noninterference and policy composition Cryptography Key management Cipher techniques Authentication Access and control mechanisms Information flow Confinement problem Introduction to assurance Building systems with assurance Formal methods Evaluating security systems Malicious logic Vulnerability analysis. Auditing Intrusion detection Network Security, Email security, IP security, and Web security. System security User security Program security.
Elective Courses
IS605: Data Mining Techniques in Smart Business [3 CH]
The course introduces the various techniques for data mining and machine learning. Some emphasis will be given to approach that are scalable to very large data sets and/or those that are relatively robust when faced with a large number of predictors, and algorithms for heterogeneous or steaming data. Many of these capabilities are essential for handing Big Data. This course provides students exposure to important developments in large-scale database systems and the analysis of this data to aid business decision making. Initial classes describe major data storage tools useful in data mining, to include data warehousing, data marts, and on-line analytic processing (OLAP). This course then discusses fundamental concepts relating to data mining, data mining applications in many business decision making contexts, and data mining software and procedure. Data mining techniques will be reviewed, with the opportunity for specific students to explore research opportunities in greater depth.
IS606: Advanced Management Information Systems [3 CH]
Explain management information systems (MIS) within a business context, with emphasis on end-user computing. Covers MIS theory and practice as they relate to management and organization theories; current trends in MIS; managerial usage of information systems; computer hardware; software, and telecommunications; information systems for marketing, finance, accounting, and other business areas; systems development process; and the role of microcomputers. Provides experiential learning by exposure to various decision-support tools for business.
IS607: Advanced Information Retrieval [3 CH]
Data management on internet: data extraction, integration, indexing, searching, clustering, and peer-to-peer; data management on wireless networks: indexing, caching, scheduling and broadcasting of data on wireless channels, modeling, indexing and querying in location-based information systems. Information Retrieval. Wireless Data Access and ISsemination. Information Retrieval on the Web. Search Engine Log Analysis. Peer-to-Peer Search. Caching in Wireless Data. Indexing Broadcast Data. Location-dependent Information services.
IS608: Geographic Information Systems and Spatial Databases [3 CH]
The fundamentals of database design and data management to support GIS and other spatial applications. Topics include modeling spatial data, spatial database design, spatial query languages, spatial database storage and indexing, and spatial query optimization.
IS609 Advanced Web Technology [3 CH]
The course focuses on the concepts of "Semantic Web", in which meaning is made explicit, allowing machines to process and integrate web resources intelligently, by reading and discussing both existing web specifications and cutting-edge research papers. Topics will include the design of various Semantic Web languages (such as XML, RDF, SHOE, and OWL), the role of ontologies and how to develop them, the knowledge acquisition problem, techniques for scalable reasoning, integrating heterogeneous data sources, web-based agents, and issues in developing semantic-aware applications, e.g. digital libraries using semantic search techniques.
DM601: Multimedia Information Systems [3 CH]
Concepts of the text/document databases, Video and Audio database Components of Multimedia Systems, Digital Audio, Video Technology and Image Compression, Computer Graphics, Multimedia Information Systems, Multimedia Communication Systems. Structure of the Internet, Methods of Storing and Accessing Data on the Internet. Multi-dimensional data structure (K-D tree, Point trees, M-X trees and R trees). Creation, and processing of multimedia databases
IS611: Advanced selected topics in Information systems [3 CH]
Topics whivh are not included in the curriculum and seems to be added. These topics are suggested as an elective subject by the council of the computer science department