100% online MSc Computer Science with Data Analytics
- 180 credits •
- 2 years part-time
This is Keele:
- 100% online MSc within 24 months
- Sought after programming and web languages taught, including Python, XML, R and Matlab
- Internationally recognised expertise in computational neuroscience, evolutionary systems, machine learning and AI, software and systems engineering
- 80% of research ‘world leading’ or ‘internationally excellent’*
- £7,440 total fees with option to pay per module
- Keele alumni discount available
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A flexible online Master’s designed to equip you for success in a data science career
The big data analytics market is forecast to grow at an annual growth rate of 29.7% and will be worth $40.6 billion by 2023 (Global Big Data Analytics Forecast to 2023, Frost and Sullivan). The online MSc Computer Science with Data Analytics from Keele University has been carefully designed to develop the knowledge and skills required to capitalise on the acute skills gap in this fast-growing area and succeed in computer science and data analytics careers.
With no prior academic or professional experience in computer science or data science required for admission, the programme is intended for proactive individuals who wish to embark on an exciting new career in this high growth field. Equally, it is also for professionals who currently work in computer science and data analytics roles and are looking for an academic qualification to accelerate their career progression.
The course equips you with sought after skills in a high demand field and prepares you to excel in a wide range of careers, from data scientist to data analyst to data engineer, at the numerous companies who are investing in the use of data collection and data analytics to support the delivery of efficient business decisions, and superior services and products, such as investment analysis, customer satisfaction analysis and the monitoring of environmental pollution.
Set yourself apart by studying with a university celebrated for academic excellence
The Keele University Computer Science and Mathematics Department is fortunate to have academics who are world-leading experts in their field and are actively involved in cutting-edge research, with 80% of the university’s research rated as ‘world leading’ or ‘internationally important’ in the latest Research Excellence Framework.
The department regularly wins and is awarded funding from the leading UK research funding agencies, ESPRC and BSRC, as well as prestigious funding bodies such as the Leverhulme Trust.
An interactive online learning experience from leaders for student satisfaction
You will learn in a highly engaging and interactive online learning environment that has been expressly designed to facilitate collaboration and peer-to-peer learning, featuring tutorials, discussion groups and online forums. Each student will be assigned a dedicated Keele Student Success Coordinator, who will provide you with all of the support you need from enrolment through to graduation.
Keele University is proud of its reputation for delivering a superb student experience and our student-centric credentials are supported by our consistent top 3 rankings for student satisfaction and course satisfaction in the National Student Survey, as well as in other surveys and rankings including the Guardian rankings (2019) and the PTES survey (2019).
What you will learn
On this data science course, you will develop an in-depth understanding of data management across a range of areas, from finance to environmental sustainability. You will study the foundations of artificial intelligence methods and advanced applications of data visualisation techniques and tools in key fields, such as smart and green energy management, global healthcare monitoring and insurance risk analysis. You will learn programming languages, including Python, R and Matlab.
Knowledge and skills taught include:
- Visualisation for data analytics
- Mathematics for AI and data science
- Statistical data analytics and databases
- Design and programming
- User interaction design
- Software engineering
- Web technologies and security
- Research and consultancy skills
A career-focused Master’s designed for a challenging and dynamic world of work
The online MSc Computer Science with Data Analytics has been designed for a global audience and can be studied from anywhere in the world. The flexible course design means that you can study around your work and family commitments and can continue to earn and progress in your role whilst you study. The course is industry-led, benefitting from the department’s collaborative projects with industry partners, such as the ‘Knowledge Transfer Partnership’, with Bentley Motors Ltd.
By studying part-time, you are able to continue working full-time and apply your learning to your current role. With six starts a year, you’re not restricted to the traditional academic year and can begin within weeks.
Key Info
Entry requirements for home and international students
You should normally have, or be about to complete:
- A 2:2 undergraduate degree or a UK master’s degree (or international equivalent).
Or:
- A third-class honours degree or an ordinary degree (without honours) or UK equivalent professional qualification with a minimum of two years’ appropriate work experience.
Or:
- Applicants who do not hold a recognised degree will be asked to provide evidence which demonstrates a minimum of three years’ relevant computing, IT or data management experience. The evidence will be assessed on a case-by-case basis.
The work experience must be at a graduate level, in either managerial or professional capacity normally in computing, IT or data-related employment which may include development, management or significant responsibility in use of IT or data.
If you earned your undergraduate degree outside the UK, you should check that it is equivalent to a 2:2.
English language requirements
If English isn’t your first language you may need to provide evidence of your English language ability. We accept the following qualifications:
- IELTS at 6.0 overall with no individual component below 5.5
- TOEFL overall minimum 79
- PTE Academic overall minimum 50
- Cambridge (CAE & CPE) overall 169 with minimum scores of 162 in Listening, Reading, Writing and Speaking
- Duolingo with 95 overall including minimum 85 in each element
- A degree qualification taught in English and completed within the last two years
Technical requirements
As these programmes are delivered 100% online, you will be required to have access to a desktop computer or laptop of which you have administrative rights which allows you to install software as required. To ensure you can engage with the programmes easily, we would highly recommend utilising a Windows, Mac, or Linux device. Access to Microsoft Office (including Word and Excel) is required (and is included at no extra cost to Keele Students), in addition to the ability to open pdf files via programs such as Acrobat.
Canvas LMS Browser and Computer Requirements
Some modules have additional technical and software requirements which include but are not limited to the following:
Design and Programming
Anaconda – accessed here
Web technologies
XAMPP – accessed here
Statistical Data Analytics and Databases
WEKA – accessed here
Programme Start dates
Fees
If you are based in the UK or the EU, you may be eligible for a government postgraduate loan to cover the full course fees.
Keele alumni discount: if you have successfully completed an undergraduate degree at Keele, you are eligible for a 10% tuition fees reduction, reducing total fees payable to £6,696.
You pay tuition fees for each module taken, either module-by-module or in full at the start of your course.
If you pay module-by-module, you will pay in instalments of £620.
Modules
Top 10
for Student Experience
(Times Good University Guide, 2020)
Award
Britain's best university, as ranked by students
(StudentCrowd University Awards, 2022)
80%
of research 'world-leading' or 'internationally excellent'
(Research Excellence Framework, 2021)
96%
Graduate Employability
(HESA Destinations of Leavers from Higher Education 2017)