MSc Data Science and Analytics

This course (previously Business Intelligence and Analytics MSc)addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course stretches the artificial intelligence (AI), machine learning (ML) and decision science themes to business intelligence, data science and business analytics.You'll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, using applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You'll also gain a greater understanding of the impact technological advances have on nature and practices adopted within data science, business intelligence and analytics, and how to adapt to these changes.Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods for data science. These include data warehousing and mining, distributed data management, and the technologies, architectures, and appropriate AI and ML techniques. The second theme will enhance your knowledge of algorithms and the quantitative techniques including AI, ML, and Operational Research (OR) suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.Teaching approaches include lectures, tutorials, seminars, and practical sessions. You will also learn through extensive coursework, class presentations, group research work, and the use of a range of industry-standard software such as R, Python, Simul8, Palisade Decision Tools, Tableau, and Oracle.Modules are typically assessed through practical coursework, which may also include an in-class test.This course has been accredited by BCS, the Chartered Institute for IT, for the purposes of partially meeting the further learning academic requirement for registration as a Chartered IT Professional. The accreditation is a mark of assurance that the course meets the standards set by BCS and it entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute. This course has also been accredited by BCS, on behalf of the Engineering Council, for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer. The accreditation is a mark of assurance that the course meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng).Careers:You'll focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, and gain a deep appreciation of the underlying models and techniques, equipping you with the practical skills needed to become a data science and analytics specialist.Typically, graduates of this course will be employed as consultants, data scientists, decision modelling or advanced data analysts, members of technicalanalytics teams supporting the decision making of middle and top management in a diverse range of sectors.

A minimum of an upper second class honours degree (2:1) or a lower second class honours degree (2:2) and substantial relevant work experience. If your first language is not English you should have an IELTS 6.5 with at least 6.0 in writing. TOEFL 88 overall with a minimum of 17 in Listening, 21 in Writing, 18 in Reading and 20 in Speaking.