Foundation of Computer & IT Systems

Introduction to the basic concepts, terminology, fields, and history of computer science, while providing students with the opportunity to develop their academic skills in studying, writing, researching, and presenting scientific topics. The course covers topics such as the history of computing, computational theory, number systems, introduction to algorithms and data structures, microprocessors, machine language and assembly, computer architecture, operating systems, compilers and interpreters, software, hardware, and networks.

Computational Mathematics

Introduction to mathematical concepts and methods primarily applied in computer science, including set theory, Boolean algebra, logic, differential and integral calculus, linear algebra, graph theory, numerical analysis, and iterative methods.

Programming

Introduction to the fundamental principles, concepts, and practices of computer programming, and the development of necessary skills for designing, implementing, and testing simple programmes. No prior programming experience is required, and all practical work is done using the industry-standard C# language and Microsoft's Visual Studio software development environment.

Fundamentals of Network & Security

The course covers the fundamental concepts of network operation, including the OSI and TCP/IP models, IPv4 and IPv6 addressing, TCP, UDP, HTTP, and DHCP protocols, routing, switching, and basic LAN network design. Additionally, the course analyzes Ethernet functions in a LAN environment and specifications for designing and building a network for a small business.

Computer Systems, Data Structures & Data Management

This course explores two related but distinct fundamental concepts of computational applications in practice: human-computer interaction and data. The course includes product design, user interface design, usability, data representation, data modeling, and data storage. Data structures and their manipulation are implemented using the Java/Python programming languages.

Scripting & Web Technologies

This course provides an introduction to modern web/scripting software development environments as a means of developing cross-platform applications, including internet-based applications. These platforms provide code-based approaches and methodologies for software development, allowing for rapid application development, including remote management and cybersecurity.

English I

Students develop general English language skills, such as reading, writing, listening, and speaking, and are introduced to academic English. They also enhance their abilities in grammar, pronunciation, and general and specific vocabulary related to computer science terminology. By the end of the course, their level of academic English will be at the midpoint of B2 according to CEFR, equivalent to IELTS 5.5.

Ethical Hacking

The course covers the principles and methods for managing and securing a LAN network from internal and external threats. The course content includes security identifiers, encryption, monitoring and interpretation of logs and alerts, implementation of firewalls, user permissions, security policies, ethical issues in policy enforcement, backup protection and fault tolerance techniques, and techniques for dealing with attacks from hackers.

Legal & Ethical Issues in Computing & Data Sciences

The course provides an introduction to the legal and ethical aspects of computer science. It covers the operation of professional bodies, including the role of codes of ethics and best practices (BCS). It then addresses the legal frameworks for data protection, privacy and security, intellectual property, and cybercrime. Students learn about the most recent applicable laws related to the use of computers and information technologies. This legislation pertains to data protection, privacy and security, intellectual property, and cybercrime.

Software Engineering

The course focuses on software development from a software engineering perspective and provides the theory and practical skills for producing software that meets user expectations in terms of quality, functionality, and development within predefined time and budget constraints. The course thoroughly examines the Software Development Life Cycle (SDLC), presenting methodologies for analysis, design, standardization, implementation, testing, installation, and maintenance of programmes.

Data Driven Systems

The course covers the development of Network Communication Systems and Protocols and how they are controlled through programming applications. Communication systems are rapidly expanding in terms of scale and capabilities, and this module examines Client-server and Peer-to-Peer systems, including Bandwidth requirements and availability. At this point, students create network protocol control applications using Java/Python. The course equips students with the necessary knowledge of programming solutions to network protocol and communication problems.

Communication & Security Protocols

This course examines data protection mechanisms suitable for various systems and architectures within the Internet, with a particular focus on cryptographic mechanisms, communication management and security measures, and network security devices. These mechanisms provide data confidentiality, integrity, as well as access control and identity verification mechanisms.

Team Project

The course aims to cultivate employability skills by introducing students to the "world of work" within a virtual business environment. Students are placed in groups representing fictional IT companies, with the goal of producing real hardware/software products and involving themselves in real operational activities. The experiences gained by students in the Team Project significantly relate to Software Engineering methodologies, such as project management, code standardization and review, design patterns, standardization, and documentation.

English II

This course builds upon the English I course and further develops students' general and academic skills in reading, writing, listening, and speaking. Students are exposed to more advanced forms of academic English and enhance their abilities in grammar, pronunciation, and general as well as specialized vocabulary related to computer science. In the end, students are expected to demonstrate a higher level of proficiency in English for academic and professional purposes.

Artificial Intelligence for Security:

This course describes the main methods and applications of AI in cybersecurity. The techniques covered include classical machine learning, linear regression, linear classifier, K-means clustering, decision trees, support vector machines, artificial neural networks, and modern deep learning techniques covering convolutional neural networks, long short-term memory networks, neural networks, and genetic networks.

Security Architectures & Future Trends:

The goal of this course is for students to understand and implement common security controls available for preventing, detecting, and recovering from security breaches and to mitigate security risks in future trend technologies. Topics covered include understanding new information technology and cybersecurity technologies, their security challenges, and approaches to addressing them, as well as understanding various security architectures.

Individual Project:

The individual project allows students to demonstrate their ability to develop a substantial piece of work related to their specialization. It can be a significant research piece following recognized research methodology or the implementation, testing, and evaluation of a significant "design and development" project in the field of computer science. Students are supported and guided by a member of the academic staff, i.e., a supervising professor, but the project is defined and implemented by the student.

Data Mining & Foundations of AI:

This module introduces students to data mining techniques and processes and the foundations of Artificial Intelligence (AI). The module prepares students for the practical use of data mining tools and the application of basic AI algorithms using the Python programming language. Students will also learn:

• Data mining processes, including data organization and cleansing, applying data mining techniques to identify patterns in data, and interpreting results from data mining tools.
• Differences in data mining techniques and determining the most suitable approach for a given real-world application.
• Fundamental concepts, uses, and techniques in AI.
• Selecting the appropriate AI method for an application.
• Using data mining tools and applying AI methods in practice.

Security Management:

This module examines strategic approaches that can be taken to manage security systems. It focuses on areas critical to maintaining security on both a daily operational basis and in crisis situations. It covers information security management and risk management related to information technology, networks, information systems, data, and critical business systems.

It covers important security management principles and functions involved in protecting an organization's critical information, network resources, and assets. It provides information on what information/network security experts would do concerning systems and policies to ensure the secure operation of networked business units and guidelines for recovery in case of a disaster.