Undergraduate Higher Diploma in Computer Science

This module covers essential topics, including computer hardware and software components, operating systems, networks, and data management. Students will develop foundational skills in using various software applications and tools, along with an understanding of the role of IT in organisational contexts. By the end of the module, students will be equipped with the knowledge and competencies necessary to effectively navigate and utilise technology in their academic and professional pursuits.

A wide range of networking technologies will be also examined including Local Area Networks (LAN) and Wide Area Networks (WAN) and how they evolved to create large-scale networks. Protocol methodologies related to IP data networks will also be explored.

This module covers the fundamental concepts of Database Management Systems (DBMS), including Structured Query Language (SQL) and PL/SQL. It also explores forms and reports, data clustering and partitioning, and the essentials of database administration.

The aim of this module is to provide learners with an understanding of current web and mobile application design technology and the practises and tools used. The learner will learn to create websites or mobile applications to give design specifications.

The aim of this module is to give learners a basic understanding of object-orientated programming languages and how to produce effective code. It also enables learners to gain a perspective of software development and the basic principles of algorithms.

The aim of this module is to give learners an understanding of software development and its evolution as an engineering discipline, and to develop, maintain, and evolve software systems of high quality.

Operational information systems are commonly structured and programmed with an object-orientated approach. Hence, this course emphasises the acquisition of fundamental skills in object-orientated programming. Theoretical concepts are elucidated and put into practise using the Java programming language.

The aim of this module is to develop learners’ knowledge and skills in managing information systems for organisations. Learners will examine how systems can be used to support core business functions, to drive business improvement, and to enable organisations to be more productive and competitive within/ the global marketplace.

The aim of this module is to develop learners' knowledge and skills in planning, configuring, setting up and managing networks (such as a LAN, PAN, MAN, WAN) as well as build skills in network monitoring, and knowledge of Network Security, network protocols and standards.

Learners will also gain knowledge and understanding about cyber security protection methods and how to manage a cyber security attack.

Emphasising Python's relevance in data science-related programming roles, the course will delve into essential topics including functions, error handling, and logging. Additionally, students will be introduced to popular data science library packages, enhancing their proficiency in Python for data analysis and related fields.

Additionally, the module introduces mathematical concepts relevant to data collection, data science, and data analysis, including data cleansing, statistical analysis, and probability, with a focus on applications in computer science and information technology.

Through theoretical learning and practical applications, students will develop the knowledge and skills necessary to effectively analyse large-scale datasets using tools like Hadoop, Spark, and R, and derive meaningful insights for decision-making processes.

Topics include conventional encryption, asymmetric and symmetric cryptology, digital signatures, certificates, key exchange, key management, authentication, network access control, cloud computing security, electronic mail security, and advanced crypto primitives. Special focus is given to emerging technologies such as BITCOIN and BLOCKCHAIN

Through theoretical insights, practical applications, and real-world projects, the module aims to equip students with the knowledge, skills, and competencies necessary to leverage data-driven approaches and AI techniques for solving complex problems across various domains.

It familiarises students with foundational terminology, engages them in discussions on typical application domains, and delves into various procedures and techniques widely used in the field.

By the end of the module, students will be proficient in implementing security measures, conducting risk assessments, and safeguarding digital assets against evolving cyber threats.

Additionally, the course will illustrate the mechanisms of data exchange, storage, and processing within IoT environments.

By combining theoretical learning with practical applications, students will develop the necessary knowledge and skills to design, implement, and evaluate machine learning models. These models will be applicable to a range of tasks, including classification, regression, clustering, and dimensionality reduction.

These components will be used to create digital systems, employing tools such as Verilog.