MSc Data Analytics and Technologies

at University of Bolton

Our team of academic and professional staff will use a variety of teaching and learning strategies to help you gain and develop appropriate concepts, knowledge and skills. You can expect practice-based enquiry, self-directed study, lectures, seminars, tutorials, presentations and work-based learning. Scheduled sessions will be held in the evening, allowing full-time and part-time students to study together and offering opportunities for those working in professional/industrial environments to present live case studies.
 

It’s important to realise that the time spent with a tutor during formally scheduled activities is only a small part of the learning time identified for a module. You’ll also be expected to spend a significant amount of time in guided independent study, such as general background reading, preparing for seminar activities and working on assignments. We are committed to supporting you throughout your learning journey. Over time, our guidance will purposefully become less structured and prescriptive. This will encourage you to develop confidence and independence in your studies and take responsibility for managing your own learning time as you increase in autonomy.
 

The assessment strategy for the programme is designed to help you achieve the overall aims of the curriculum, as well as the learning outcomes for individual modules. As well as assessing your achievement, it helps to organise and develop your learning. Assessment feedback can help you develop your skills and an understanding of your strengths and weaknesses.
 

The types of assessment you’ll be required to complete fall into two general categories: formative and summative. Formative assessments help in learning and developing knowledge and skills. Summative assessments, on which grades are allocated, reflect the quality of the learning that has been achieved. Formative assessment will take place via tutorial discussion, group workshops including peer and tutor review, and guidance on work in progress. Formative feedback will be provided face-to-face via discussion, online or in written form. Summative assessments consist of both practical and applied theoretical work. These will include a range of assessments including practical projects, written work, presentations and portfolios.
 

Modules

The modules listed below may be a mixture of compulsory and optional. You may not have the opportunity to study all the modules shown as part of the course.

• Data Science
• Big Data Technologies
• Research Methods
• Masters Project
• Solutions Design and Ethical Practice
   

• You should have at least a lower second class (2.2) honours degree (or equivalent) in any subject or five years’ relevant work experience.
• You must also have GCSE Mathematics at grade C or above or grade 4 to 9. Please contact us for details of other acceptable qualifications. If you don’t have an acceptable mathematics qualification, you’ll need to attain a minimum mark in a diagnostic mathematics test.
• If you wish to gain admission on the basis of five years’ relevant work experience, you’ll be required to attend an online or face-to-face interview and present evidence in the form of a portfolio of work and examples that demonstrate your suitability and aptitude for the course. The evidence should be presented in electronic format and attested by an independent person. The independent person could be a current or former lecturer or an employer who has a more senior role than yourself. The University is looking for candidates who can demonstrate a clear style and commitment to their professional practice and who will benefit from experiencing this area of study.
• We'll consider applications where appropriate work experience can be demonstrated in lieu of, or in addition to, the published academic qualifications in line with the University’s Recognition of Prior Experiential Learning (RPEL) procedures.
• If English isn’t your first language, you’ll also need IELTS 6.0 with no less than 5.5 in any band (or equivalent). 

Overseas students starting this course in the first year will be required to pay a Overseas fee of £12,950

Data is rewriting the rules of many professions and employers from government departments to technology start-ups are scrambling to recruit professionals who can help them make sense of it. The demand for workers with specialist data skills is enormous. The UK data market was £1.1 billion in 2018 – the largest in Europe and the second largest in the world (3). Organisations from across the economic spectrum are seeking to recruit people with data science skills and the opportunities for professionals continue to grow.
 

Our MSc Data Analytics and Technologies offers a postgraduate route into this in-demand and varied career. It also acts as a bridge into data analysis and technologies if your undergraduate degree was in an unrelated subject area. Additionally, it’s an excellent option if you’ve been working in a relevant field gaining degree-level knowledge through experience and self-study rather than formal education. You can join this course without ever having studied data or computing before.
 

As a graduate of this master’s degree, you’ll possess an impressive all-round combination of skills and knowledge. In addition to a strong theoretical and practical knowledge of data analytics and technologies, you’ll be able to demonstrate essential interpersonal and people skills, such as collaboration and team working, negotiation and persuasion. You’ll have a clear understanding of the contexts in which data analysts work, coupled with commercial awareness and business-relevant knowledge. You’ll also possess high-level academic skills in research, critical thinking and curiosity. Not only will all this help you become established early on in your career, but you’ll also be primed to take on leadership roles. Moreover, you’ll have the lifelong learning, problem-solving and decision-making skills needed to adapt to new challenges throughout your career.