Data Science MSc

• The key educational aim of the programme is to prepare students for a variety of leading roles in data science. Such roles will involve data-intensive computing and lead to positions as data scientists, data analysts, data engineers and data architects, as well as business analysts and database administrators, with expected progression through to managerial roles involving teams of these. Creation, collection, management and analysis of data is core to a wide range of industry activities, from politics to advertising, health, finance, and numerous others., This Master's Degree programme is studied full-time over one academic year, consisting of 180 credits at FHEQ level 7. All modules are semester based and worth 15 credits with the exception of project, practice based and dissertation modules. Possible exit awards include:

• Postgraduate Diploma (120 credits)

• Postgraduate Certificate (60 credits) some programmes may contain up to 30 credits at FHEQ level 6., This Master's Degree programme is studied full-time over two academic years, consisting of 240 credits at FHEQ level 7. All modules are semester based and worth 15 credits with the exception of project, practice based and dissertation modules. Possible exit awards include:

• Postgraduate Diploma (120 credits)

• Postgraduate Certificate (60 credits) *some programmes may contain up to 30 credits at FHEQ level 6., Computers are embedded within almost every industry including industries such as energy and agriculture to enhance sustainability. As part of the MSc Dissertation module, students have the opportunity to work in many areas including supporting the UN Sustainability goals.

• The programme incorporates an optional year in industry in order to foster close engagement with the employers of data scientists. This offers an attractive proposition to employers and provides students who have completed the taught programme, and whose subsequent assessment relates to practical experience, with access to potential employers following graduation. An extension to the dissertation emphasises the importance of clear business understanding of value being derived from research and development., The principles and practices of data science K PGCert, PGDip, MSc The principles and applications of data science technologies K PGCert, PGDip, MSc The professional issues involved in the exploitation of data K PGCert, PGDip, MSc The areas of emergent and innovative data science technologies K PGCert, PGDip, MSc The key research issues in data science K PGDip, MSc Understand, articulate, and demonstrate how to achieve the requirements of the users of data science applications C PGCert, PGDip, MSc Research, develop, and evaluate data science methods C PGDip, MSc Specify, design and develop solutions to complex and substantial data science problems C PGDip, MSc The practices and business relevance of data science P PGCert, PGDip, MSc The ability to critically evaluate software systems and tools P PGCert, PGDip, MSc The capability to work as an effective member of a team P PGCert, PGDip, MSc The ability to communicate effectively with specialists and non-specialists to understand their needs P PGCert, PGDip, MSc The ability to apply and justify appropriate ways to analyse data and present information P PGDip, MSc The ability to plan, research, manage and implement a major project P MSc Research and information retrieval skills T PGCert, PGDip, MSc Numeracy in both understanding and presenting cases involving a quantitative dimension T PGCert, PGDip, MSc Self-learning skills T PGCert, PGDip, MSc Succinctly present, to a range of audiences, knowledge relevant to the building, testing and deployment of a system T PGCert, PGDip, MSc Time management and organisational skills T PGCert, PGDip, MSc Effective use of specialist IT facilities T PGCert, PGDip, MSc Continuing professional development T PGCert, PGDip, MSc, COMM070 - MSC DATA SCIENCE DISSERTATION

Second semester (semester 1 according to the academic calendar) you will study these THREE compulsory modules: COMM034 - CLOUD COMPUTING COMM076 - DATABASE SYSTEMS AND BUSINESS INTELLIGENCE COMM071 - STATISTICAL DATA SCIENCE, COMM070 - MSC DATA SCIENCE DISSERTATION

You will also study ENGM324 - EMPLOYABILITY

Year 2 (full-time with placement - 2 years) - FHEQ Levels 6 and 7

Module code Module title Status Credits Semester COMM063 PROFESSIONAL POSTGRADUATE YEAR (DATA SCIENCE) Core 60 Year-long COMM070 MSC DATA SCIENCE DISSERTATION Core 60 Cross Year

Module Selection for Year 2 (full-time with placement - 2 years) - FHEQ Levels 6 and 7

COMM063 - Professional Postgraduate Year (Data Science) COMM070 - MSC DATA SCIENCE DISSERTATION, Strong technical skills are critical to being a data scientist and this programme provides a solid technical grounding in the practical side of data science. Modules such as Business Analytics with Data Visualisation or Machine Learning for Data Science give students experience solving technical problems with industry standard languages such as Python and R and using real world data sets wherever possible. In the Master Dissertation module, students get the opportunity to design and develop a technical solution to a problem of their choice. Digital skills are key for many industry jobs and this programme aims to develop both the foundational underpinning as well as industry ready digital skills.

Employability This Data Science programme provides the foundational theory and practical skills that allow our students to work in a range of different industries such as tech, or finance. Wherever possible we use industry standard languages such as Python and R to provide students with the practical skills that will allow them to compete for technical data science and AI jobs. On top of this, we ensure students have an understanding of the fundamentals of data science as this will allow them to apply their knowledge to new technologies and new situations. Where possible, we work with real world problems and modules such as Business Analytics with Data Visualisation will allow students to work together to solve a large scale problem in a situation similar to what would be expected of them in an industry context. This programme offers a placement option which gives students the benefit of a year working in industry to improve their employment prospects.

Global and Cultural Skills Computer Science is a global language and the tools and languages used on this programme can be used internationally. Students learn work together in groups with other students from different backgrounds to solve a problem. These programme allows students to develop skills that will allow them to build applications with global reach and collaborate with their peers around the world.

Resourcefulness and Resilience This programme requires practical problem-solving skills that teach a student how to reason about and solve new unseen problems starting with a problem scenario and designing and developing a complex and practical solution to the problem. A typical coursework will present a scenario with a data set (often in real world context) and ask students to develop a solution to processing and analysing the data. This requires not just technical development skills but the planning and problems-solving skill to approach a large problem, break it down into smaller chunks and solve and integrate these chunks into a working solution. We encourage an open ended nature to our practical work where possible. This encourages students to go beyond the taught material and deliver innovative solutions to large scale problems. A module such as Machine Learning for Data Science teaches students how to work in group to plan and execute a complex project. The MSc Dissertation module requires student to use these skills to take an idea concept through to implementation and write a professional report detailing their work.