Module Descriptors

Core modules

Informatics Research Methods:

The module aims to teach the methodologies of and the skills for conducting research in Informatics. It will focus on three main parts: (1) analytical methods; (2) empirical methods; (3) writing and evaluating research. The module will cover the nature of Informatics and Informatics research; criteria for assessing Informatics research; different methodologies for Informatics research and how to combine them; analytical proof; algorithm and complexity analysis; the design of experiments and evaluations; practical advice on conducting research and numerous research skills including: reading, reviewing, presenting, writing, and design .

Knowledge Representation and Reasoning:

This module provides the basis for the understanding and use of Knowledge Representation and Reasoning techniques in AI systems in general, and knowledge-based systems in particular. The module covers notions of representation and the relationship between representation and that which is represented, along with issues of the resources required to manipulate such representations. The focus is on different logic-based representation languages and proof search using logical calculi, but other approaches are also discussed.

Introduction to Computational Linguistics:

This course provides an introduction to the basic theory and practice of computational approaches to natural language processing. The module covers the following topics: introduction to programming in Python and NLTK; tokenisation; part-of-speech tagging; context-free grammars for natural language; evaluating a natural language processing system; parsing techniques; information extraction; Arabic language processing. The course also provides an introductory insight into the state of current research in Computational Linguistics.

Data Mining and Exploration:

Data mining is about analysing, interpreting, visualising and exploiting the data that is captured in scientific and commercial environments. The course features presentations and each student will undertake a mini-project on a real-world dataset.

Elective IT Modules (2 are taken)

IT Project Management:

This module is about IT project management activities. Covered topics include software systems engineering, project planning and management, quality assurance, and strategic planning. Students will learn to manage software as a distinct project, use specifications and descriptions, make use of structured techniques, complete reviews and audits, confirm product development with planned verification, and validation and testing. Students will work with essential tools and methodologies for managing an effective IT project, including software for version control, and project management.

Knowledge Management:

The aim of this module is to teach the principles and technologies of knowledge management. A case study approach, as and where appropriate, will be adopted in introducing the course contents. The module covers the fundamental concepts in the study of knowledge and its creation, representation, dissemination, use and re-use, and management. The focus is on methods, techniques, and tools for computer support of knowledge management, knowledge acquisition, and how to apply a knowledge management system using one of the knowledge-based system tools.

Knowledge Engineering:

This module introduces a variety of methodologies important to the development of modern knowledge-based systems (KBSs) and their applications, especially pertaining to the Semantic Web. The module covers topics regarding different processes within a KBS lifecycle, ranging from knowledge capture and analysis, systems design and implementation, to knowledge maintenance and system evaluation. Students will learn about the latest applications of KBS in building intelligence into web applications, and will build a knowledge-based web application.

Machine Learning:

Machine learning is about making computers learn, rather than simply programming them to do tasks. The course will discuss supervised learning (which is concerned with learning to predict an output, from given inputs), reinforcement learning (which is concerned with learning from interacting with an environment), unsupervised learning (where we wish to discover the structure in a set of patterns). We will compare and contrast different learning algorithms. In this course, we will get to the technical and mathematical details of the studied algorithms.

E-Commerce:

This module is about topics related to creating a business on the web, with particular focus on e-commerce. Students will study the IT issues raised by electronic business and commerce. Techniques and technologies available for designing and implementing e-business and e-commerce applications will be surveyed. Students will have first-hand experience with web-based tools and services to help design e-business solutions.

IT Entrepreneurship:

This module provides students with scientific methodologies for identifying opportunities in the IT space. Students will learn how to create an effective business plan, acquiring funding, establishing a company from scratch and managing in an environment of high growth, high uncertainty and rapid change. The module will include case studies of successful and failed IT entrepreneurial companies and will draw upon guest speakers from the angel investing, venture capital and entrepreneurial communities.

Software Systems Design:

This course is designed to give students knowledge of the principles of object-orientation and extensive practice in the application of these principles using the Unified Process (UP) and Unified Modelling Language (UML). The course will also give students knowledge of Model Driven Architecture (MDA). MDA is the future of UML and unifies every step of software systems development and integration from business modelling, through architectural and application modelling, to development, deployment, maintenance, and system evolution.

Systems Requirements Engineering:

The course describes the role of requirements in the construction and continued maintenance of large, complex and evolving software-intensive systems. It introduces the important concepts and activities in systems requirements engineering, explains how they can knit together to form a through-life requirements engineering process, and demonstrates how such an end-to-end process can be defined and used in practice. The course provides a broad overview of the notations, techniques, methods and tools that can be used to support the various requirements engineering activities, and complements this with the opportunity to gain experience in a selection of these.

Management Information Systems:

This module is about determining the needs for designing and implementing information systems that support these needs. Management information systems integrate, for purposes of information requirements, the accounting, financial, and operations management functions of an organisation. This course will examine the various levels and types of software and information systems required by an organisation to integrate these functions.

The British University in Dubai

Block 11, 1st and 2nd floor, Dubai International Academic City PO Box 345015, Dubai, UAE

Tel: +971 4 279 1400

Whatsapp: +971 50 701 2843

Email: [email protected]