Programmes / Masters and MBA Programmes / Master of Science in Informatics / Module Descriptors
The aim of this module is 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, design, etc.
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.
This is an introductory course that presumes no prior familiarity with Computational Linguistics. This course provides an introduction to the basic theory and practice of computational approaches to natural language processing. The module cover the following topic: introduction to programming in Python & NLTK, tokenization, 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 is about analyzing, interpreting, visualizing and exploiting the data that is captured scientific and commercial environments. This module provides students with an opportunity to gain an in depth understanding of the theories and issues related to mining and exploring data, ranging from statistical summaries, to visualization, to classification and clustering. Practical case studies will be used for illustration.
This module is about IT project management activities. Covered topics include software systems engineering, project planning and management, quality assurance, and strategic planning. The student 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.
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.
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 about learning from interacting with an environment), unsupervised learning, where we wish to discover the structure in a set of patterns; there is no output “teacher signal”. We will compare and contrast different learning algorithms, and unlike Data Mining Exploration module where the focus was on the applying algorithms to large real-world data sets, in this course we will get to the technical and mathematical details of the studied algorithms.
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.
This module provides the 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 the angel investing, venture capital and entrepreneurial communities from guest speakers.
This module is about determining the information system 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 organization. This course will examine the various levels and types of software and information systems required by an organization to integrate these functions.
The information and communications technologies are advancing at an ever-increasing rate. The whole world is now interconnected. This module provides postgraduate students with an opportunity to gain an in-depth understanding of the theories and issues on some recent trends in informatics themes. This course will enable the students to appreciate the scale of new developments and create prototypes of applications in their desired ambit. The course should cover new technologies that are not offered in other offered module descriptions (e.g., Energy Aware Computing, Bioinformatics, Health Informatics, Intelligent Systems, Cyber Security Threat Analysis, Cyber Defence Forensics, to name a few.)
Having successfully completed the six modules in the taught stage of the programme, students who wish to proceed to the master’s degree take the dissertation stage. This final project is intended to give students an opportunity to focus on an aspect of the taught subject matter and investigate it in more detail. This will help them consolidate their capacity for independent study, and to learn some of the techniques needed to conduct research and develop knowledge in the subject area of the programme of study.
This is a research project. The only piece of work to be submitted for examination is a dissertation, and this is a written report on the research. There are thus two aspects to consider: the research and the writing. Both are governed by implicit rules common to the discipline of formal research; part of the students’ training is to become familiar with these rules.
In this module the student will undertake a short research project. This project could be an extension of one or more projects submitted in previous modules. In this module the student will reflect on all his/her research activities in the previous modules, will undertake critical review of previous outcomes in order to prepare a proposal for new research project. The student will focus on applying the knowledge learnt in several modules to analyse, revise, improve and assess a relevant topic. This could include topics on Artificial Intelligence, Intelligent Systems, Knowledge Management, Learning from Data, Software Engineering, IT & management, or any other relevant IT topic as long as it is approved by the module tutor. The student will produce a research report, including an executive summary, reflective analysis of previous works, and details of the project outcome.
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