Module details

First year | Second year | Third year

First year modules:

 

Block 1: Foundations of Computing

This module introduces students to the professional context of computer science, software engineering, cyber security, and digital forensics. It introduces mathematical structures that provide a basis for computer science and cyber security to prepare students with the necessary skills in this domain. Students gain skills to learn the concepts of computer science cyber security.  

In this module the students will learn the mathematical foundation of computing such as Logic and Boolean Algebra, Set Theory, Probability and Statistics, Relations, Functions, and Modular Arithmetic. The evolution of computational IT infrastructures (e.g., general-purpose mainframe and minicomputer computing, personal computers, client/server networks, enterprise computing, cloud, and mobile computing.) will also be presented and discussed from hardware, software, OSs, applications, data management and storage internet platforms.  

Lecture: 24 hours
Seminar: 48 hours
Self-directed study: 156 hours
Consolidation: 40 hours
Revision: 30 hours
Assessment: 2 hours 

Total 300 hours

Block 2: Programming in Python

The Python programming module has no pre-requisites; it is designed for learners with no prior programming experience and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. As well as covering the basics of how one constructs a program from a series of simple instructions in Python, this module aims to teach students the basics of programming computers using Python.  

Students will be introduced to fundamental theories and related concepts of the Python programming language; the module will help the learner develop a sufficiently rich and detailed, generally applicable background and hands-on practical knowledge. Learners will solve problems, explore real-world software development challenges, and create practical applications. 

Workshop/Lectures: 40 hours 
Practical/Large Group: 72 hours 
Self-directed study: 136 hours 
Assessment: 52 hours

Block 3: Data Analytics and Statistics

Introduces the skills on data analytics and basic quantitative techniques for data collection, summary and presentation. Students will develop an understanding of basic concepts associated with the analysis and interpretation of statistical data within a business and organizational context.  

This module will allow students to understand and present financial data within a business and organisational structure.  Students will be able to apply financial mathematical techniques to simple but real life scenarios to make decisions. The module will also introduce the formulation, solution and interpretation of linear programming models and cover network models and project management.  

Lecture: 24 hours  
Seminar: 24 hours  
Practical: 24 hours  
Self-directed study: 180 hours  
Assessment: 48 hours

Block 4: Information Systems Analysis and Design

This module gives an insight into the many tasks that must be carried out during the analysis and design stages of an information system development project. It provides a practical introduction to the techniques used at different stages of a project. It also illustrates how these tasks fit together within the overall project framework, and how they can be managed to ensure that the aims of the project are met. 

Lecture: 24 hours
Seminar: 24 hours
Practical: 24 hours
Self-directed study: 104 hours
Assessment: 60 hours

Second year modules:

Block 1: Advanced Data Analytics and Visualisation

This module builds on the introduction to the Python programming language and data analytics modules that are studied at Level 4. In this module further data analytics using Python is taught, covering a wide range of analytics including text analytics, predictive analytics and sentiment analysis. The module will also include the use of Python for data extraction, storage and analysing textual and numeric data. Visualisation is also covered alongside data analytics in this module. 

Lecture: 5 hours
Seminar: 6 hours
Practical: 35 hours
Workshop: 18 hours
Self-directed study: 86 hours
Consolidation: 60 hours
Reading: 40 hours
Assessment: 50 hours

Block 2: Operational Research

This module aims to introduce a range of techniques, that typically fall under the headings of Operational Research, Management Science or Decision Science, which can be used as part of an effective and pragmatic decision-making process. The techniques covered include a selection of the more popular and commonly applied methodologies which have wide ranging applications such as optimisation methods, and forecasting, amongst others. The emphasis throughout is on the formulation (structuring) of real problems and the development of practical solution using computer software. 

Lecture: 22 hours 
Seminar: 22 hours 
Practical: 22 hours 
Self-directed study: 190 hours 
Assessment: 44 hours 

Block 3: Introduction to Information Security  

The module will investigate the importance of Information Security in the context of Information Systems. The module will be investigating the challenges to application and system developers in relation to the requirement for secure design and implementation. The module is a foundation of security foundations as required in terms of requirements analysis and the design of software. The module will be providing a theoretical framework in providing security solutions with reference to secure application development. 

Lecture: 15 hours
Seminar: 30 hours
Self-directed study: 55 hours
Assessment: 50 hours

Block 3: Information and Database Development

In an emerging digital world, data is essential to all aspects of human life. What is of more importance, is how data is efficiently stored, retrieved, and presented in a way that makes sense. using appropriate database management systems (DBMS). This module will take students through the fundamentals of DBMS, shedding light onto the two broad categories of DBMS: relational (structured) and non-relational (unstructured) databases. Students will understand the business and technical motivations behind the use of specific DBMS for managing information in specific situations. 

Practical: 10 hours
Lecture: 20 hours
Tutorial: 10 hours
Reading: 20 hours
Collaborative: 10 hours
Reflection: 20 hours
Revision: 20 hours
Assessment: 40 hours

Block 4: Integrated Project

The module will take the form of a taught project module allowing students to draw up the specification, documentation and early prototype for a constrained system. Student will be encouraged to work in teams providing opportunity to experience modern techniques such as Agile/Scrum development. Although no specific language is explicitly named for the module it would be wise to select a family of languages / development environments that allow student to demonstrate a range of modern technical skills. 

Practical: 48 hours
Lecture: 24 hours
Collaborative: 40 hours
Revision: 40 hours
Consolidation: 148 hours 

Third year modules:

Block 1: Advanced Statistics for Business

This module emphasis on simple and multiple linear regression and regression analysis. It also emphasis on decision analysis, time series analysis and forecasting, optimization and the information to be found by the categorization of data into discrete groupings with similar properties. Integrating the underlying theory with a thorough practical grounding using modern laboratory software, students will be taught to formulate and model the problems mathematically. They will learn to apply standard software packages, such as Excel LP Solver, Minitab, SAS etc. Students will be trained in presenting, interpreting and critically analyzing the result of the problems. 

Learning, teaching and assessment activity hours for the module:  

Lecture: 11 hours
Seminar: 11 hours
Practical: 11 hours
Self-directed study: 57 hours
Assessment: 60 hours

Block 2: Advanced Business Modelling

This module provides an overview of data analytics practices and their implications in businesses. Analysing business cases and running hands on-experiments on data, we explore how organisations leverage new data resources to develop and implement emerging business ideas, innovating the process of value creation and transforming their relationships with their customers and other stakeholders. The module delves into business practices, structures and processes that leverage big data generated in organisations to create value. 

Lecture: 12 hours
Practical (Q&A): 12 hours
Self-directed study: 106 hours
Assessment: 20 hours

Block 3: Business Systems Solutions

The aim of this module is to provide students with the essential knowledge to critically evaluate IT decisions that are made at managerial level. Students will explore the implications of digital transformation, and the changing roles of the C-Suite to accommodate global changes in the business environment. The role of IT and different solutions available to a business, based on their need will be discussed; for example, enterprise systems, cloud-based systems, and business intelligence/analytics solutions.

With the growing role of data and emerging technology, students will also explore the importance of strategic, tactical and operational decision-making and the role of business analytics in supporting the business problem solving process. Finally, students will also explore and understand the ethical implications of IT, which influence the decisions around how IT is designed, implemented and used in an organisation. 

Block 4: Final Year Project

The Final Year Project enables students to undertake an individual project on an approved topic of interest, that addresses significant Computing and Information Systems related problems relevant to the Programme of study. The Project provides an opportunity for the students to integrate many of the threads of their Programme of study and to extend their work beyond the taught elements through with research and self-learning.

Lecture: 8 hours
Online interactive workshop: 8 hours
Supervisor meetings: 5 hours
Self-study: 219 hours
Assessment: 60 hours

Optional modules (select one) 

Privacy and Data Protection 

There continues to be a growth of databases holding personal and other sensitive information in multiple formats including text, pictures and sound. The scale of data collected, its type and the scale and speed of data exchange have all changed with the advent of ICT. Whilst the potential to breach privacy continues to increase organisations are subjected to a considerable amount of legislation governing privacy and data protection.  

This module examines the balance between maintaining business effectiveness, legal compliance and professional practice in the field of IT/IS.  

The module will address the legal, social and technological aspects of privacy and data protection, consider privacy enabling technologies and privacy invasive technologies and identify and evaluate the role of the computer professional in providing privacy and data protection. 

Lecture: 40 hours
Seminar: 90 hours
Self-directed study: 90 hours
Assessment: 80 hours

Advanced Database Management and Programming

Based on modules studied in previous years involving databases and computer programming, this module provides the student with further training on the essentials of advanced database management and programming, developing the student's ability to differentiate between relational databases and non-relational databases. 

It develops the skills to choose a suitable database for an application from a business perspective to meet stated requirements using realistic scenarios and the ability to analyse semi-structured data and to choose an appropriate storage structure. It also develops skills in database design and data retrieval using a variety of complex data structures and NoSQL programming including aggregation methods.

Practical: 20 hours
Lecture: 40 hours
Online learning: 60 hours
Reading: 60 hours
Reflection: 60 hours
Revision: 60 hours

Data Mining

Data mining is fast becoming essential to the modern competitive business world. This module aims to review the methods available for uncovering important information from large data sets; to discuss the techniques and when and how to use them effectively.  

The module uses the data mining tool SAS Enterprise Miner. SAS is a comprehensive data management software package that combines data entry and manipulation capabilities with report production, graphical display and statistical modelling. 

Lecture: 20 hours
Practical: 40 hours
Self-directed study: 200 hours
Assessment: 40 hours

Information and Communication Technologies for Development

This module will expose students to issues that influence the adoption, implementation, uptake, and sustainability of ICTs (Information and Communication Technologies) in developing countries. Students will recognise the historical perspectives to the ICT4D concept and why it offers significant possibilities towards addressing some diverse development issues, but also at times exacerbating these existing issues.

Students will learn how to apply theoretical frameworks, such as (but not limited to), the ICT4D value chain, stakeholder matrix, and responsible research and innovation (RRI), in the analysis of ICTs issues and appraisal of ICT implementation solutions and uptake status of a developing country. In addition, the module will discuss the United Nations (UN) Sustainable Development Goals (SDGs) and debate how ICTs might, if at all, progress these Goals.

Lectures: 50 hours
Seminars: 30 hours 
Reading: 40 hours
Collaborative: 20 hours
Reflection: 40 hours
Revision: 40 hours
Assessment: 80 hours 

Note: All modules are subject to change in order to keep content current.