Modules

This module introduces the structure and operation of the various system components including the CPU, system buses and internal/external memory, with an emphasis on programming techniques and/or access mechanisms for those components. An overview of numbering systems and digital logic will complete the architecture section. In the second part of this module, students will apply their acquired knowledge to the design of an operating system (OS). Students will also learn how various OS features are applied in the Windows 2000/XP and UNIX operating systems.

Prerequisites: None

This is intended as a foundational programming module, suitable for students with no previous experience of computer programming as well as those with moderate previous knowledge or knowledge of languages other than C. It will provide students with a solid foundation in the key concepts of functional programming, as well as an appreciation of object-oriented programming. The emphasis is on applied problem-solving skills as well as on the theoretical concepts underlying the programming activity. Although the module focuses specifically on the C language, students who have successfully completed it will typically find learning other high-level languages relatively easy, having learned the important skills and concepts of programming in this module.

Prerequisite: Computer Architecture and Operating Systems

This module will provide students with the fundamental software engineering knowledge necessary to develop and deliver quality software products. This course provides an overview of the development of software systems: software engineering encompasses technology, business, organisational and human concerns. The course brings together the various software components (technology) and the diverse issues impacting their development (process, project, people) to improve software product quality. The challenges of successfully completing software development projects will be addressed, practically (best practice with regard to methods, tools and techniques), empirically (based on actual findings) and theoretically (informed by a number of Software Engineering laws).

Prerequisite: Fundamentals of Programming or Object Oriented Programming

This module provides detailed coverage of Object Oriented (OO) programming principles. It focuses on programming in Java, an OO language that is modern, vendor-independent, and widely used in industry. Recognising that programming requires skill as well as knowledge, this module places emphasis on the practical aspects of developing significant Java programs using a professional development environment. Students learn how to model objects in software, define classes describing categories of objects, and make appropriate use of concepts such as inheritance, composition, encapsulation, polymorphism, abstract classes, and interfaces. As well as learning basic Java syntax and how to express OO concepts in Java, practical topics such as applets, graphics, data storage, multi-threaded programming, and exception handling are addressed.

Prerequisite: Fundamentals of Programming

This module provides a comprehensive introduction to the field of Object Oriented Design and the Unified Modeling Language (UML). The application of UML is explored from analysis through design and on to final system implementation, highlighting the strengths of object orientation as an approach to systems development, where the one notation is used throughout. Students will develop object oriented analysis and design models using Computer Aided Software Engineering (CASE) tools, similar to those developed in the Software Engineering module.

Prerequisite: None

The module will provide students with a good understanding of how to design and implement internet based distributed applications. The emphasis will be on explaining and evaluating the standard APIs and frameworks that are commonly used. The module will cover the essential Java language features and APIs that are needed to create network based applications; I/O streams and multithreaded programming support in Java; and the various APIs and frameworks that are used to implement distributed applications.

Prerequisite: Object Oriented Programming

This module is an introduction to some of the fundamental concepts and techniques in Artificial Intelligence (AI). The module begins by examining the concept of AI and as well highlighting some important real-world applications of AI. It then presents search strategies currently employed in AI research. This is developed further by the examination of the functional programming language Prolog. The second half of the module looks at Knowledge Representation and Machine Learning. It also deals with the topic of uncertainty in AI. Finally, the module finishes by examining future directions of AI research and associated philosophical dilemmas.

Prerequisite: None

This course is designed to introduce Databases while outlining the differences between Data and Information and the methods used for Data Retrieval versus those used for Information Retrieval.  Various techniques are models are examined such as the Boolean Model of Information Retrieval.  The module covers Document Processing in terms of Stemming and Indexing before discussing Evaluation Approaches, Collaborative Filtering, Web Search and Document Clustering.

This module introduces Databases, outlining the differences between Databases and File Systems and considering the importance of Abstraction.  Concepts, Integrity Constraints and Design Principles for the Relational Model are investigated. 
The module also covers Relational Algebra, Querying, Structure Query Language (SQL), Conceptual Modelling, Relational Schema and Normalisation.

This module begins with a review of Relational Design Principles before moving on to look at Efficiency in terms of Indexing and Query Optimisation.  Further Design Principles such as Armstrong's Axioms, Closure, Minimal Cover Sets, Synthesis and Normalisation are covered.  Transactions and a variety of Database Models are examined.

This module introduces Data Mining before getting into the detail of the subject area with the following topics:

• Data Preprocessing
• Association Rules
• Classification
• Evaluation
• Clustering