The course has been co-designed with IT professionals in Data, Business, Business Intelligent Analysts, Data Manager and IT Data security roles across the UK and Europe. This is a great learning opportunity for STEM and near STEM graduates to become Data Project Managers.

Anne Nortcliffe, Head of School of Engineering, Technology and Design

    How do you want to study?

    Duration:

    1 year

    Location(s):

    Canterbury
    ApplyBook an Open Day

    Overview

    The Big Data revolution needs data professionals to assist in data intelligence through automated data management, analysis and presentation in industry and public sector, as the increase in demand is 160% (Blau, 2015; Columbus, 2017). 

    Typically computing courses in the UK don’t address industries’ and public sectors’ need for data professionals to manage data for public good. There is an increase in demand for graduates with interdisciplinary skills and abilities; social science humanities, mathematical, information science, systems science, psychology and economics. 

      All about the course

      This course has been co-designed with industry to ensure the course learning is industry-relevant and will develop your learning in inclusive data intelligence and management for public good. The course provides learning opportunity for numerically literate non-STEM and near STEM graduates to develop technical and professional skills in data intelligence at Master’s level: computer programming, data visual analytics, artificial intelligence, data in action, big data database development, and Geographical information systems.

      This course will also address the considerate and responsible use of data for public good, legal, ethical and social issues of Big Data, and equip you to be the next generation of data science professionals to question and address social bias of data, unethical and legal issues. This area of data science is growing, (Saqr, 2017), as industry and public sector addresses their systems to be more inclusive. Industry is aware and willing to address these issues and are seeking data scientists who are responsive, enthusiastic, collaborative, creative and logical to conceive, design, implement and operate Big Data solutions, and work within and developing the emerging policies to the benefit of all stakeholders. 

      Entry requirements

      You should be a digital and numerical literate graduate with a degree (2:2 or higher) in:

      • STEM degree subjects or near STEM subjects (examples of near STEM subjects include: Economics, Informatics, Accountancy)
      • Non-STEM degree subjects: if your degree is not related to STEM, you will also need an A level in maths.

      For more information on the IELTS (International English language Testing System) requirements for this course, please click here to visit our dedicated web page.

      More information about entry requirements.

      Module information

      Core/optional modules

      *Modules subject to validation

      How you’ll learn

      This MSc follows elements of the Conceive-Design-Implement-Operate (CDIO - www.cdio.org) strategy. Key to this is the industrial relevance of the programme. You will take part in active learning, working with peers collaboratively to coordinate and yield solutions to interdisciplinary group projects/projects that are typically sourced from industry. The MSc will develop both technical and employability skills; interpersonal, management, leadership, emotional intelligence. The blended learning approach of lectures and workshops face-to-face and online will:

      1. Use industrially recognised and relevant technology.
      2. Receive guidance and other interaction with Industrial Partners – including in assessment where possible. 
      3. Build the level of complexity of problems and yield interesting solutions over the period of the degree programme through working on and solving where possible industry sourced problems/projects.
      4. Consider Data in Action for emergency, societal, humanitarian, and environmental public good.

      The course will consist of blend of online and face-to-face campus practical learning in computing laboratories and face-to- face and online theoretical and practical learning.

      The MSc will build upon the skills you developed as an undergraduate, and encourage the development of an enquiring mind, technical and employability skills to systematically solve and critically analyse complex problems.

      Digital Learning Environment

      The online and on campus practical learning in the MSc will use open source, student licensed software (which we (the School) have invested in) and cloud-based software resources, for example computer programming using Jupyter Hub and Python. The course will also utilise Blackboard Virtual Learning Environment to support online asynchronous and synchronous online video learning, discussion board, chats, in conjunction with digital learning tools like Mentimeter, Socrative, Kahoot, YouTube, Padlet, MS Whiteboard, MS Teams, GitHub, MS Visual Studio Live, etc.

      Each 20 credits module will require:

      • 40 hours scheduled timetable contact learning
      • 40 hours guided self study learning
      • 120 hours self study learning

      Professional Research Methods and Project 60 credit module will require:

      • 28 hours scheduled timetabled contact learning
      • 572 hours self study learning 

      I particularly like the inclusion of: Data in action, Big Data Database Development and the introduction to AI for data science.

      Callum MulliganOperational Analyst at UK Ministry of Defence

      How you’ll be assessed

      You will be assessed by both coursework and computer based assessments, essentially the programme is 100% coursework assessment. The coursework assessments will enable you to demonstrate the development of your key scientific and transferable skills. The course typically consists of coursework assessments submissions of (but not exclusive): computer scientific lab, logbooks, on-line quizzes, written reports, written scientific papers, discursive essays, stand-alone video presentations, walkthroughs, digital artefacts and poster presentations and professional portfolio.

      Feedback

      Assessment feedback will be provided through use of (but not exclusive) assessment rubric, written, audio recording, self/peer, one to one face to face, group face to face, tutorial, video conference, dragon den, panel interview, video, screencast, and computer-generated feedback.

      100% Coursework

      Your future career

      Career opportunities include:

      • Charities are in need of Data Intelligent professionals to help empower social change campaigns to the identification of empathetic target audience for increase revenues streams.
      • Commercial organisations value Data Intelligence to identify business opportunities, spot trends, evidence for decisions and when to flip business and rapid transformation operations to ensure continuous sustainable economic growth, for example identification of new business location that has sustainable local demand, raw materials, logistics and potential employees with the right skill sets.
      • Government ministries like the Ministry for Health and Social Care are employing Data Scientists to identify improvements in health care and public health functions policy and practice to automate and increase efficiencies of medical diagnostic solutions.
      • Environmental agencies employ Data Scientists to identify and predict environmental challenges and priority areas to be addressed.
      • Government and businesses valued Data Scientists informing the science of spread, hotspots and behaviour of virus pandemic as Data Science helps to inform the science further, identify risks factors, solutions, policy and practice.
      • Data Architecture for online retailers, designing automated data analysis data models to support business strategic data needs of understanding optimising business retail revenue streams and improvements.

      Fees

      Government loans of up to £11,570 are available for some postgraduate Master’s courses for students starting their course from 1 August 2021. Loans are subject to both personal and course eligibility criteria.

      The rules around course eligibility mean that in some cases it may depend on how you are studying (full-time or part-time) as to whether you can apply for a postgraduate loan. To check whether your course is eligible, you can email the Student Fees Team or call 01227 923 948.

      2022/23 tuition fees for this course

        UK Overseas
      Full-time £8,250 £14,500
      Part-time £4,125 N/A

      20% Alumni Discount

      We offer alumni discounts on CCCU Postgraduate Taught, PGCE Primary and Secondary, and Masters by Research courses for eligible students.

      Find out if you're eligible for the discount.

       

      Important Information on Tuition Fees

      Tuition fees for all courses which last more than one academic year are payable on an annual basis, except where stated.

      There will be an annual inflationary increase in tuition fees for this course where the course lasts more than one academic year. For further information read the 2022/23 Tuition fee statements and continuing fee information.

      Apply now

      Duration:

      1 year

      Location(s):

      Canterbury
      Apply