Compulsory courses

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Internet of Things

Lab.: (-)

This course gives a foundation in the Internet of Things, including Introduction to IoT, the components, tools, and analysis by teaching the concepts behind the IoT and a look at real-world solutions, its applications, architectures, and technologies, logical Design of IoT, physical design of IoT, IoT Enabling Technologies, IoT & deployment templates, IoT and M2M, Big Data in IoT Systems, IoT Security Techniques, Domain Specific IoTs (Home Automation – Cities – Environment – Energy – Retail – Logistics – Agriculture – Industry – Health & Lifestyle)

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Human-Computer Interaction

Lab.: (-)

This course is concerned with designing interactions between human activities and the computational systems that support them, with constructing interfaces to afford those interactions, and with the study of major phenomena surrounding them.

Interaction between users and computational artifacts occurs at an interface which includes both software and hardware. Thus, interface design impacts the software life-cycle in that it should occur early; the design and implementation of core functionality can influence the user interface for better or worse.

HCI draws on a variety of disciplinary traditions, including psychology, ergonomics, computer science, graphic and product design, anthropology and engineering.

The course considers a variety of methods that can be applied to the design and evaluate interactive systems.  The emphasis of the course is on practical understanding, application and evaluation of HCI concepts and methods.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Security and Privacy

Lab.: (-)

As specialized computing devices and applications rapidly proliferate into many aspects of everyday life, including: automotive, household automation, computerized manufacturing, and medicine. This course covers modern security and privacy aspects in Cyber-Physical Systems (CPSs). Therefore, the main objective is for students to identify when security (confidentiality, availability and integrity) is required and to be able to choose and implement right solution in CPSs. The course includes overview of terminology and basic concepts in security and privacy, attaining familiarity with range of CPS security threats, examples of concrete attacks, risk management, security technologies and tools, cryptography, security protocols involving CPS components, security policies and standards, wireless security, intrusion detection and prevention, and selected security topics. The essence of the course concentrates on recent developments in security and privacy in CPSs.  As a result of rapid development in this field, the exact list of topics is expected to change every few years.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Embedded Systems

Lab.: (-)

This course is structured to combine lectures, case studies and tutorials for the students to gain an in-depth understanding of fundamental concepts and knowledge in embedded/cyber-physical systems. This course presents an overview of: design flow, special characteristics with respect to specification techniques and modeling, embedded hardware, standard software, evaluation and validation, mapping of applications to execution platforms, optimizations and testing of embedded/cyber-physical systems.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Machine Learning/Deep learning

Lab.: (0)

Machine learning can be described as the artificial generation of knowledge from experience, where an artificial system will learn from examples. The technology will not just memorize, but will recognize and learn specific patterns and laws relating to the natural phenomena.

This course provides the fundamentals of machine learning applied on image processing, pattern recognition text and video analysis. After getting the basics of machine learning by training and deploying neural networks, common aspects and architecture of deep learning applied to objects detection, text analysis and pattern recognition will be provided. Evaluation protocol and model validation are focused too.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Entrepreneurship

Lab.: (0)

The entrepreneurship and innovation course aim at providing the students with the needed knowledge to take their innovation ideas to the next step and possibly form a small company or a business. The course will cover the main entrepreneurship fundamental topic such as: idea creation, team building, conduct a successful market research, presenting the idea,  determining the competitive advantage, idea protection and Intellectual Property (IP) , monetization and different business models, raising funding and approaching investors, conducting a successful  financial analysis, writing a business plan, creating a prototype or a proof of concept, launching a betta marketing the idea, receiving the customer feedback and improving the product/service.

Specialized Elective Coureses

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Big Data Analysis

Lab.: (-)

This course provides the basics of big data analysis. The course begins with a basic introduction to big data and discusses what the analysis of these data entails, as well as associated technical and conceptual challenges. The second part focuses on providing a theoretical and practical introduction to big data, its analysis and associated challenges. The last part of the course includes practical exercises in order to develop and present a big data concept for a specific real-world case and provide a first experience in handling and analyzing large, complex data structures.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Real time systems

Lab.: (-)

The course addresses basic concepts of real-time systems, presents examples of real-time systems, covers real-time systems analysis and design, and gives an in-depth treatment of timing analysis and scheduling. The course is organized around the issue of real-time requirements and their impact on the architecture of a system.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Control systems

Lab.: (-)

 Modeling, analysis and design of cyber-physical systems (CPS). The course serves as an introductory graduate level-class for students interested in CPSs in general, and control and optimization of CPSs in specific. The fundamentals of CPSs are covered in the class, with emphasis on the control and the optimization aspects. Covered CPS topics include:  linear and nonlinear systems theory and design, state-estimators, fault-tolerant controllers and observers, optimal control and networked control systems.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Sensors and Actuators

Lab.: (-)

This course studies actuators and sensors commonly used in the design of Embedded Systems. A balance between the modeling / analysis and the hardware implementation of these various devices is emphasized. Actual Embedded systems from industry and academia are used to demonstrate actuator and sensor use. Actuators studied include: brushed dc motors, stepper motors, brushless dc motors, solenoids, hydraulic and pneumatic actuators.

Analog and digital sensors studied include: optical encoders, Hall-effect sensors, potentiometers, variable-inductance transducers, permanent magnet transducers, eddy-current transducers, variable-capacitance transducers, and piezoelectric transducers. Smart sensors and actuators are discussed.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Computer Vision

Lab.: (-)

This course provides the fundamentals of computer vision, image processing, pattern recognition and video analysis. A first the, course covers the basics of the image formation process. Then, the course includes topics of image such as filtering, the Fourier transform, wavelets, geometric transformations and feature detection. The last part of the course is focused on motion analysis and video processing. Topics of this part include mainly: motion estimation, object detection tracking. The course presents also typical computer vision applications such as image segmentation, object recognition, face detection, vehicle and people tracking.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

dependability (safety, reliability and availability)

Lab.: (-)

The course introduces the main terminology, concepts, and principles for designing, measuring, and evaluating, quantitatively, the dependability of CPSs. The main topics are covered in this course: Dependability attributes: availability, reliability, and safety and modelling and analysis approaches for dependability of CPSs. Also, the failure process and fault handling and maintenance with focusing on: first, available effective tools, metrics, and techniques for predicting the hardware and software failure rates and modelling of software failures. Second, applying the effective architectures. Furthermore, evaluating the serviceability of computer networks.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Cloud Computing

Lab.: (-)

This course aims to provide an overview of cloud computing where fundamental and advanced concepts are introduced. Topics include cloud deployment models, cloud system architectures and X-as-a-Service notion, cloud storage and management, virtualization and resource management. Privacy issues and Security concepts including common cloud security threats and risks are also covered. Students will use and explore cloud computing platforms developed by Google, Amazon and Microsoft. Examples of cloud programming paradigms such as Hadoop’s MapReduce are covered.  Students are also exposed to recent research topics on cloud computing and carry on presentation on these issues.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Wireless Communication Networks

Lab.: (0)

This Course introduces a comprehensive overview of different Wireless Communication Networks Technology and Standards with an emphasis on the following topics: Satellite Communication Networks, Cellular Wireless Networks, Cordless Systems and Wireless Local Loop, Mobile IP and Wireless Access Protocol, Wireless Local Area Networks Technology (WLANs), Wi-Fi and IEEE Wireless LAN Standards, Bluetooth and IEEE Standards, Personal Area Networks (PANs) and Ad hoc networks.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Distributed Systems

Lab.: (-)

This course introduces basic and advanced knowledge to give an understanding how modern distributed cyber-physical systems operate. The course explores recent trends exemplified by current highly available and reliable distributed systems.
The focus of the course is on distributed algorithms and on practical aspects that should be considered when designing and implementing cyber-physical systems. Topics covered during the course are: architectures of distributed systems, process of distributed systems, synchronization and coordination algorithms, replication, and end-to-end system design communication, naming, fault tolerance and security.
Computer based assignments are used extensively to give students practical experience in designing and implementing distributed cyber-physical systems.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Mobile and Ubiquitous Computing

Lab.: (0)

This course explores the area of ubiquitous computing (and allows students to work on a variety of small technology projects. Students will be exposed to the basics of building Ubiquitous systems, emerging new research topics, and advanced prototyping techniques. This course incorporates a combination of topics covering a wide variety of disciplines that impact ubiquitous computing. These include human-computer interaction (HCI), machine learning, embedded systems, signal processing, tangible computing, electronics, and sensors. The emphasis is on developing deeper understanding of the functioning of mobile wireless networks, mobile sensing, pervasive computing and applications of mobile systems. The course examines these systems both from a technical perspective, as well as in terms of interdisciplinary applications, thus touches upon machine learning, computer network analysis, and healthcare. Students are introduced to development tools and techniques for building mobile systems and their understanding is reinforced through practical work in modern technology.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Industrial Communication Protocols

Lab.: (-)

with the introduction of the Internet of Things (IoT) and cyberphysical system (CPS) concepts in industrial application scenarios, industrial automation is undergoing a tremendous change. This is made possible in part by recent advances in technology that allow interconnection on a wider and more fine-grained scale.

This course focuses on industrial automation networks. It builds upon knowledge and skills developed in undergraduate courses on data communication systems typically covering traditional local area network protocols such as Ethernet and higher-level protocols such as TCP/IP. The major differences between industrial networks and traditional computer networks are considered in detail. Factors influencing the choice of industrial communication protocols for given applications are analyzed and Quality of Service (QoS) parameters are deduced and evaluated.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Low power networks

Lab.: (0)

This course gives an overview on wireless sensor networks (WSN) and how they enable the Internet of Things (IoT). WSN are networks of embedded devices, such as sensors, that have limited power, memory, and processing capability. These low-cost devices are often battery operated and can only handle limited amounts of data. Due to the embedded nature of these devices, they are subjected to a high variance of environmental factors, interference, and noise. Network protocols must be designed to operate effectively in what is referred to as a “lossy” environment where transmitted messages are often lost. WSN have broad applications for remote sensing or surveillance. Applications of WSN include the Internet of Things (IoT), Machine to Machine (M2M) communications, and Smart City. Most important is that it enables these devices to connect to the Internet. However, it also allows these devices to leverage standard Web-based interfaces and standard management tools, as well as being able to leverage a suite of support protocols such as IPsec for security and ICMP for control messaging. This course will take the learner through the different protocols that make up this exciting world of interconnected things.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Mobile Communication Networks

Lab.: (0)

This course provides a comprehensive overview of the mobile communication networks. The course starts with a brief history of the mobile communications, the evolution of the mobile generation technology, and introduces the multiple access techniques. The cellular concept is also discussed in detail featuring frequency reuse, channel allocation strategies, interference management, handoff strategies, power control, traffic intensity, and cellular capacity improvement techniques. The mobile radio propagation large-scale and small-scale path losses are analyzed, and the link budget design is calculated based on different path loss and fading models. The course mainly focuses on the specifications, key features, network structures, and radio resources management of the key mobile communication systems (namely: GSM, UMTS and LTE-A).

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Network Optimization

Lab.: (0)

In this course a modern theory of optimization for dynamic networks is presented.  The focus is on computer and wireless networks, including networks with time varying channels, mobility, and randomly arriving traffic.  Applications to operations research and economics are also considered. The general theory of optimization is developed for constrained optimization of time averages.  This is applied to problems such as queue stability, network utility maximization, efficient energy allocation, profit maximization, inventory control, stock market trading, and other problems involving dynamic decisions.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

Software Engineering

Lab.: (0)

This course provides advanced training in computer science engineering to design, understand, develop and maintain complex software systems.  It includes the following topics: agile methods (scrum, XP, UP….), software requirements, project management, verification and validation and testing, computer aided software (case tools), software measurements, software quality.

Lect.: (3)

Credit Hours

3))

Course Code

Course Title

semantic web

Lab.: (0)

In fact, in the last decade, the Web moved away from a purely document-centric information system to one in which hypertext techniques are applied to the sort of data found in databases; Semantic Web technologies enable people to create data stores on the Web, build vocabularies, write rules for handling data, and develop systems that can support trusted interactions over the network. This module looks at the development of the Semantic Web, at the technologies underlying it, and at the way in which those technologies are applied. The Semantic Web represents the next major evolution in connecting information. It enables data to be linked from a source to any other source and to be understood by computers so that they can perform increasingly sophisticated tasks on our behalf.
This course will introduce the Semantic Web, putting it in the context of both the evolution of the World Wide Web as well as data management in general, particularly in large corporations.

This course provides advanced training in semantic web.  It includes the following topics: RDF, SPARQL, OWL