This module looks at different data processing and mining techniques and state of the art data processing and mining tools. The topics include introduction to data mining and knowledge discovery process, data collection and processing with various data types from variety of sources, social web mining. The module will look at a variety of techniques and trends in data mining.

Data visualisation is an important visual method for effective communication and analysing large datasets. With the rapid increase of the data volume and complexity, users find that it is very difficult to understand and make sense of the data. Through data visualisation, data is presented in a meaningful and interactive way to users, so that users can draw conclusions from data that sometimes are not immediately obvious, and hence manipulate and use the data in for exploring, learning, communicating, solving problem and decision making. Specialist software (SAS) will be used during each week of the module, and you'll use SAS to prepare your final assessment. The module will provide students with the knowledge of theoretical concepts of interactive data visualisation and presentation, creative design process as well as the applications of interactive visualisation and presentation tools and techniques

The material in this module is carefully designed to meet students’ needs and requirements for the programme of study alongside essential project management skills dictating research activities. Students will be exposed to a wide variety of tools, techniques, methodologies and processes in the field of project management. Ethical and legal aspects of project planning and management will also be discussed.

This module introduces students to research, and methodologies used to underpin scientific work, data analysis, hypothesis’ establishment and artefact validation in understanding research on an appropriate subject discipline. The material in this module is carefully designed to meet students’ needs and requirements for the programme of study. This module covers traditional approaches in literature review as essential preparation for the project stage and draws expertise from other departments within the University.

This is an introductory course in statistics for data science and as such it assumes little prior knowledge of the subject. This module introduces the basics of descriptive statistics (including graphical methods), estimation, linear regression models and inferential statistics. Appropriate software tools will be used to will be used to extract insights from data.

The manipulation and management of data is fundamental to data science and artificial intelligence. This module aims to equip students with the skills necessary to design and implement appropriate database systems to support the manipulation of data and keep it secure. The module will also provide an understanding of the different types of database systems to allow an understanding of where they are applicable.

This module is designed as an introduction to some of the central concepts and tools used in Data Science. As such it includes discussions on data capture, maintenance, processing, analysis and communication. A series of real-world case studies will be discussed, and state of the art software and algorithms will be used as tools within these case studies.

Whether you decide to progress to further study or to a career in industry, one of the most important skills expected of a Data Scientist is the ability to work creatively under the appropriate guidance of an organisation. It is therefore essential that you use and develop the skills and knowledge gained from other modules and from your wider educational and/or working background in a major integrative exercise. You will be expected to develop an idea (guided by a member of academic staff) and demonstrate your ability to develop it further, producing a suitable artefact by applying your technical, analytical, practical and managerial skills in an integrated manner.