Overview
Get the postgraduate edge with an MSc in data science. As Artificial Intelligence and the Big Data revolution continue to grow, the need for data intelligence professionals is in more demand than ever.
On this Master's in Data Intelligence course, you will undertake a holistic approach to Big Data as you study how to manage data for public good. Due to the demand for graduates who maintain interdisciplinary skills within humanities, mathematics, informational science, systems science, psychology, and economics, you will engage with a range of industry-led content that will enable you to extract, analyse, and visualise data.
Not only will you grasp a solid understanding of AI, data in action, Big Data database development, and geographical information systems, you will also learn how to responsibly use this data, whilst taking legal, ethical, and social aspects into consideration.
The need for graduates with a MSc in data science is vital – industry seeks data analysts who are responsive, enthusiastic, collaborative, creative, and logical, which this Master’s degree focuses on.
MSc Data Intelligence with placement
Our MSc Data Intelligence with placement module offers a fantastic opportunity for you to gain professional work experience to complement your academic studies.
This will introduce you to professional practice through workplace learning, which will enhance both your personal development and future employability.
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 IELTS web page.
Module information
As well as the core modules, you may also have the opportunity to study a number of option modules in your second and third year. Option modules will not be pre-selected for you. We provide examples of option modules. The availability of specific option modules may vary from year to year. The offer of an option will be subject to a minimum number of students choosing the module to ensure the appropriate student experience. The offer of option modules may also be affected by staff availability. It means we cannot guarantee the availability of a particular optional module. However, we will ensure you have a choice of option modules.
Core/optional modules
How you’ll learn
This MSc follows elements of the CDIO (Conceive-Design-Implement-Operate) 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 Data Intelligence MSc will develop both technical and employability skills, interpersonal skills, management, leadership, and emotional intelligence. The blended learning approach of lectures and workshops face-to-face and online will:
- Use industrially recognised and relevant technology.
- Receive guidance and other interaction with industrial partners, including in assessment where possible.
- 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.
- 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 in Data Intelligence will build upon the skills you developed as an undergraduate and encourage the development of an enquiring mind, and 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 and cloud-based software resources, for example computer programming using Jupyter Hub and Python.
The course will also utilise the Blackboard Virtual Learning Environment to support online asynchronous and synchronous online video learning, discussion board, and 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 .
Data Intelligence Placement 0 credit:
- 10 hours pre-placement preparation scheduled contact (during trimesters 1 & 2)
- 10 hours guided independent learning (during trimesters 1 & 2)
- 40 hours independent learning (across trimesters 1 to 3)
- Placement/work-based learning (undertaken in trimester 3)
- Non-student route visa students: Minimum 240 hours, Maximum 480 hours (e.g. 20 – 40 hours over 12 weeks).
- Student route visa students: Minimum 384 hours, Maximum 480 hours (e.g. 32-40 hours per week over 12 weeks).
I particularly like the inclusion of: Data in action, Big Data database development and the introduction to AI for data science.
Callum Operational 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 assessment 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
- poster presentations and professional portfolio.
Feedback
Assessment feedback will be provided through use of (but not exclusive): assessment rubric
- written and audio recording
- self/peer feedback
- one-to-one and group feedback
- tutorial
- video conference
- dragon den panel interview
- video
- screencast
- computer-generated feedback.
MSc Data Intelligence placement
The placement can be either paid or unpaid, and is identified either by you or via the course team. All placements must be approved by the course team before they commence. The placement module will provide guidance on preparing, identifying and applying for placements/internships before the placement is undertaken during Trimester 3.
Student Route visa students’ placements will require a minimum of 384 hours to a maximum of 480 hours throughout the Trimester (normally 32-40 hours over 12 weeks) to ensure visa compliance. All other students will require a minimum of 240 hours to a maximum 480 hours throughout the Trimester (normally 20-40 hours over 12 weeks). The weekly schedule and location are flexible in accordance with the student’s personal circumstances and the needs of the employer (External or Internal to University).
On completion of the placement you will return to University for a further Trimester to undertake your final modules.
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 locations that have 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 healthcare 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 and optimising business retail revenue streams and improvements.
Fees
Government loans are available for some postgraduate Master’s courses. 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 923 456.
Tuition fees for this course without placement year
| UK | Overseas | |
| Full-time | £9,545 | £15,500 |
Tuition fees for this course with placement year
Placement year fee: £850
| UK | Overseas | |
| Full-time | £10,395 | £16,350 |
20% Alumni Discount
We offer alumni discounts on CCCU Postgraduate Taught, PGCE Primary and Secondary, and Master's 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 Tuition fee statements and continuing fee information.