This course provides knowledge and skills of problem solving and introductory programming using Java programming language. Topics cover: the problem- solving process; data types; variables, constants, and scope; simple sequential programs; basic input/output; selection and repetition control structures; arrays and strings; user-defined methods, and Input/output file processing.
This course covers the essential mathematical topics that students specialized in information technology need. The first part of the course deals with plane analytic geometry. The second part covers the basic knowledge about matrices and determinants. The third part is designed to provide students with notions of real functions: limits, continuity, differentiability, and integration with applications on simple derivatives and integrals.
The course introduces students to fundamentals of discrete mathematics and statistics that IT professionals should acquire. The course covers relevant topics in sets, functions, relations, number systems, logic, hypothesis, vector and matrices, and statistical sampling. The course also introduces students to basic terminologies of trees, and graph theory.
The major role of information technology (IT) is to support organizational personnel, regardless of their functional area or level in the organization. The aim of this course is to provide students with solid grounding in business uses of information technology in a rapidly changing environment, and to provide discussion of critical issues surrounding the use of IT in organizations. This course covers a range of general information technology topics that will make the student appreciate the role of IT in business. Topics include: information technology fundamentals; information technologies; computer networks and security; business applications; development processes; and ethical, societal and security issues.
The primary objective of this course is to introduce the concepts of object-oriented programming: classes, objects, methods, object interaction, encapsulation, inheritance, polymorphism, composition, recursive algorithms, and exception handling. This course is not meant as a comprehensive introduction to all of Java concepts such as applets and socket programming.
This course introduces the phases of the System Development Life Cycle. Topics covered include: Systems Development Methodologies, System Project Planning; Requirement Analysis; System Design; Human Computer Interaction Layer Design; Physical Architecture Layer Design; and Implementation Phase. Systems analysis and design using UML will be discussed theoretically.
This course is designed to give students a comprehensive knowledge of computer architecture at the hardware and software levels. The students will learn the fundamentals of computer organization and architecture, covering the topics related to operating system, processor, memory locations and operations, addressing modes, instruction types, number representation, digital logic, CPU Basics, Registers, Control Unit, Cache Memory, Input/output and parallel systems.
The course covers the Abstract Data Types (ADT), as well as the design and implementation of data structures such as arrays, stacks, queues, linked lists, binary search trees, and graphs along with algorithms that make use of such structures including algorithms for sorting, searching, and recursive solutions will be studied. Algorithms will be analyzed in terms of time complexity will be considered as well. Students will write programs that embody these data structures and algorithms.
This course provides an introduction to computer networks and the Internet. It also introduce students to Protocol layers and the OSI model, Network models, Network Performance, Switching and Network Devices. Data Link Layer: ARP, Error Detection and Correction, Data-link Control, Medium Access, Ethernet, WLANs, Network Layer: IP and Routing Algorithms, Transport Layer: UDP, TCP, Congestion Control, Application Layer: Web, FTP, e-mail, DNS and P2P..
This course introduces the fundamentals of client Web systems technologies to students. Topics covered include: XHTML, CSS, XML, and JavaScript, Students will apply this knowledge to generate essential web components like basic browser controls (buttons, links, and menus), forms and frames.
This course builds on students’ soft skills attained throughout the university years including written and oral communications, the ability to apply technology in learning, critical thinking and problem solving in order to lead a group of people or an organization to achieve a short term goal related to a project or a generic mid-term goal. Student will apply feedback elicitation to gauge success of approach and make amendments as necessary to achieve more effective results; both peer feedback and instructor feedback will be utilized for this purpose. The course will also involve the students in discussions, debate, presentations and seminars in order to create opportunities to assess each other’s work and give feedback. There will be a final report/essay and presentation that reflects and summarizes the benefits of successful activities and lessons learnt from others.
This course will introduce the basic concepts and skills needed to extract knowledge from data. The students will learn the basics of statistical interference and machine learning needed to analyze the data. Students will learn concepts, algorithms and tools they need to deal with various facets of data science, including data exploratory analysis, data science process, feature generation and feature extraction, data visualization, and the ethics of data science.
This course covers the principles and concepts of modern operating systems. Operating system services: processes and process management, memory management, file systems, Input/Output and device control, deadlocks, and case studies. To introduce the student to the principles and practice of operating systems with respect to effective and convenient management and operation of a computer operating system.
This course is designed to give a theoretical and practical background in database techniques. It covers database concepts, data models, data dictionary, entity relationship diagrams, and the relational data model, converting E-R models to relational model, SQL language, normalization, and physical database design. Oracle software is used in the Lab.
This course aims at introducing fundamental security concepts to students. Basic security concepts such as CIA model and cryptography techniques in security information system will be introduced. Other topics include: Authentication, Access Control, Database Security, Malicious Software, Denial of Services Attack, and Network Security. Students will also learn the legal and ethical aspects of information security.
This course will introduce students to the new type of Internet application that endeavors to make the thing’s information (whatever that may be) available on a global scale. The course covers the building blocks of Internet of Things (IoTs) and their characteristics. A Taxonomy of IoT systems is proposed comprising of various IoT levels with increasing levels of complexity. The student will be able to describe domain specific Internet of Things and their real-world applications. The course covers the programming aspects of Internet of Things and packages, frameworks and cloud services. Student will examine various IoT domains.
This course will examine the ethical issues that arise in the use of computers, and the responsibilities of those who work with computers, either as computer science professionals or as end users. Topics covered include: legal, social and ethical issues surrounding computer technology and its use; privacy; intellectual property rights and copy right laws; information technology code of ethics; issues of privacy and confidentiality; risks of using computers; and computer crime: computer viruses, hacking, phishing & pharming, scams.
This course covers concepts and issues related to information technology project management. Main topics of the course include: Project management processes and integration, Project management scope, time, cost, quality, human resource, communication, risk and procurement management. Students will be able to apply appropriate legal and ethical standards in any IT related project.
This course aims to introduce students to theory and practice of cloud computing. Topics include: parallel and distributed systems; deployment and service models; cloud infrastructure; applications and paradigms; resource virtualization; management and scheduling; networking support; cloud storage systems; and cloud security.
The course introduces students to principles and guidelines needed to develop interface designs. The course covers theoretical foundations and design processes such as usability of interactives systems, user interface requirements, interaction style and evaluation and user experience.
This is an introduction to the technologies that are used for big data. The aim of the course is to provide students with the knowledge required to use big data technologies and learn how to store, and process big data sets. Topics covered include: Big Data and Spark stack, Hadoop, Hadoop Distributed File System, Map Reduce, PIG, HIVE, SQL, HBASE, Searching for data, and Big Data Management Challenges.
The aim of the course is to develop practical client side and server side programming, design and management skills used in the creation and updating of dynamic content systems. This course will help students to develop a detailed understanding of the client/server architecture of web based database publishing systems, the range of databases, and scripting languages available for the development of such systems. The students will be able to identify the role of dynamic content as used by a broad spectrum of organizations across a range of industry sectors.
Today’s IT deals with gigantic amount of information. The success of any organization greatly depends on its ability to process and understand its information and extract essential knowledge to help managers take well-informed decisions. This course teaches students the basic of data warehouse and how to deal with business intelligence – an information technology approach to data collection, data storage and data analysis to support a wide variety of management tasks, from performance evaluation to trend spotting and policy making. The students learn effective modeling techniques and use them to extract business intelligence and present them to users.
This course introduces mobile applications development. Students will be able to learn the development of mobile applications for cell phones and tablets. Main topics of the course include: Eclipse for Android Software Development, Android applications and building a view in Android, drawing 2D and 3D graphics and handling and persisting data during the application development process.
This course is designed to introduce the theory and techniques of AI to students. The course covers: knowledge representation schemes, classical and heuristic search techniques, inferencing, machine learning, and agents. The PROLOG language is also covered to enable students to represent, manipulate, and reason with knowledge.
Students shall design, implement, test and demonstrate their graduation project in two semesters. Graduation Project I is to be completed in first semester in the field of specilization and it includes literature survey, action plan, design of complete project taking into account realistic constraints, computer simulation (if applicable), partial implementation and testing. The course also includes report writing and oral presentation.
This course is a continuation of Graduation Project I in the second semester. In this course, students will complete the implementation and testing of the remaining part of their solution. They will integrate the complete project, test it, and prepare a Report, oral presentation, poster presentation, and project demonstration.
This course provides practical advanced data analysis and deep learning approaches using Python language. The students will learn data handling tasks such as fetch data, data cleaning and retrieve data from different resources. Students will learn regression, statistical learning techniques, linear models and unsupervised approaches. Further the students will be introduced to different deep learning architectures and develop neural network models such as Convolutional Networks (CNNs), and Recurrent and Recursive Networks(RNN).
The success of any organization greatly depends on its ability to process and understand its information and extract essential knowledge to help managers take well informed decisions. This course aims to introduce students to concepts and techniques of Data Mining. Main topics include: Data mining concepts and tasks, classification techniques, association analysis and algorithms, clustering analysis and algorithms, anomaly detection methods, avoiding false discoveries and web mining.
This course builds on top of the first DBMS course by introducing advanced database concepts to allow students to effectively design and implement a database. The course revisits SQL in a deeper, more practical approach, with a focus on its PL/SQL extension. The student will learn object oriented database design, and how to manage multi-user databases with respect to concurrency and recovery. Also, students will be exposed to database optimization and performance evaluation.
This course covers data visualization, the art and science of turning data into readable graphics. Student will know how to create data visualizations based on data available and tasks to be achieved. Student will learn visualization techniques for abstract data, scientific visualization techniques for spatial data, use of space and color to visually encode data in a view, and the trade-offs between changing a single view and using multiple linked views, and the ways to reduce the amount of data shown in each view.
This course aims to introduce students to new developments in the area of data analytics not specifically covered in the curriculum and in which a faculty member has developed interest and proficiency. The intention is to provide a rapid response to current trends and to widen student’s knowledge in different areas of Information Technology. Specific content of the course will depend on the particular area taught at the time.
|
No. |
Name |
Rank |
Degrees Held |
Conferring institution |
|
1 |
Haytham Elmessiry |
Associate Prof. |
Ph. D. of Nature Sciences. Computer Science |
Ulm university |
|
2 |
Liaqat Ali |
Associate Prof. |
Ph. D. Information System |
University of East London |
|
3 |
Mohammed Salahat |
Assistant Prof. |
Ph. D. Information System |
University of Huddersfield |
Student-Full Faculty Ratio by Colleges for fall semester2022-2023 (2022-1)
|
College |
Student-Full Time Faculty Ratio 2022-1 |
|
College of Engineering and Information Technology |
13.11 |