Data Science and its Applications (Medway), MSc
Our MSc degree in Data Science and its Applications is designed to provide students with a solid grounding in data science theory and practice.
Our MSc in Data Science and its Applications course has been designed to increase the skilled workforce and diversity of qualified data science experts in the global market regardless of your academic background.
Whether transitioning into data science roles or exploring specialised areas, this course equips you with practical skills to analyse, solve, and evaluate data-heavy projects – essential for both employment and further studies. Explore a range of captivating topics in modern data science and apply your data handling skills to real-world issues across various fields.
This one-year full-time, 2-year part-time course offers flexibility with optional modules in different data science applications, allowing you to tailor your learning to your interests and career goals. Graduates find opportunities in private and public companies, government, and non-governmental organisations. Join us on this dynamic learning journey and unlock the potential of data science for your future career.
This course also offers scholarships (£10,000 each) that are available exclusively for UK domicile students who are female, black, disabled, or from a low socioeconomic background (Index of Multiple Disadvantage quintiles 1 and 2, low household income).
You can choose to study this course at either Greenwich Campus or our Medway Campus.
Location
Duration
- 1 years full-time
- 2 years part-time
Start month
September; January
Home/international fees 2024/25
£11,000 /£18,150
What you should know about this course
What you will study
Full Time
Year 1
Students are required to study the following compulsory modules.
- Databases and Data Infrastructure (10 credits)
- Ethics and Governance (10 credits)
- Group Project (30 credits)
- Individual Project (30 credits)
- Machine Learning and its Applications (15 credits)
- Principles of Data Science (15 credits)
- Programming for Data Science (15 credits)
- Research Project Management (10 credits)
- Mathematics and Statistics for Data Science (15 credits)
Students are required to choose 30 credits from this list of options.
- Advanced Programming for Data Science (15 credits)
- Data Science for Medical Applications (15 credits)
- Data Visualisation and its Applications (15 credits)
- Graph Theory and its Applications (15 credits)
- Spatial Data Science (15 credits)
Part Time
Year 1
Students are required to study the following compulsory modules.
- Machine Learning and its Applications (15 credits)
- Programming for Data Science (15 credits)
- Mathematics and Statistics for Data Science (15 credits)
Students are required to choose 15 credits from this list of options.
- Advanced Programming for Data Science (15 credits)
- Data Science for Medical Applications (15 credits)
- Data Visualisation and its Applications (15 credits)
- Graph Theory and its Applications (15 credits)
- Spatial Data Science (15 credits)
Year 2
Students are required to study the following compulsory modules.
- Databases and Data Infrastructure (10 credits)
- Ethics and Governance (10 credits)
- Group Project (30 credits)
- Individual Project (30 credits)
- Principles of Data Science (15 credits)
- Research Project Management (10 credits)
Students are required to choose 15 credits from this list of options.
- Advanced Programming for Data Science (15 credits)
- Data Science for Medical Applications (15 credits)
- Data Visualisation and its Applications (15 credits)
- Graph Theory and its Applications (15 credits)
- Spatial Data Science (15 credits)
About the course team
The programme team are experienced academic and industry professionals, with many years of experience in various aspects and applications of Data Science. Our teaching is informed by research and consultancy work, as well as by the latest teaching best practice.
I studied English Language and Linguistics as my first degree. I chose to study this Postgraduate degree as it is geared towards students from a non-STEM background.
I studied a PhD in Sociology, coming from a social science background I was looking for something that was more cushion learning into data science. I find the modules interesting and the university is very diverse.
I’ve never been to university before, I pursued a vocational path in accounting. I find the course syllabus compelling. I will gain knowledge and learn how to apply it, this will help me pursue a career in data science.
Come and meet us
We are offering virtual events so that you can still experience how Greenwich could be the right university for you.
Next Open Days
Got a question?
To find out more about our Open Days and Campus Tours or if you need any assistance, please email opendays@gre.ac.uk.
Entry requirements
You should hold an undergraduate (honours) degree at 2:2 or above, in any non-STEM (e.g economics, business, arts) or far-STEM subject (e.g. biology, geography, psychology, medicine), and GCSE Mathematics grade 4/C or equivalent.
Applicants who hold an undergraduate or postgraduate degree in the same broad subject area as this course (e.g computer science, AI, data science) or in a core-STEM subject (e.g. physics, engineering, mathematics, statistics, IT) will be considered for MSc Data Science, a specialist course designed for applicants with this background.
Additional requirements
Priority will be given to applicants who are women, black, disabled or from low socioeconomic background (Index of Multiple Disadvantage quintiles 1 and 2, low household income).
Please note: to be considered for scholarships, specifically available to students on this course, applicants must:
- apply to the course by the scholarship deadlines, and
- provided a personal statement as part of your application to the course explaining which of the scholarship eligibility criteria you meet, why you are applying for the course and the scholarship, and how you think this scholarship will help you on the course and your future aspirations (300 words maximum).
For more information, contact courseinfo@greenwich.ac.uk or 020 8331 9000.
You can also read our admissions policy.
Available to overseas students?
Yes
Can I use Prior Learning?
Find out more on our Recognition of Prior Learning pages.
How you will learn
Teaching
In a typical week, learning takes place through a combination of lectures, tutorials and practical work in the labs. You'll be able to discuss and develop your understanding of topics covered in lectures in smaller group sessions, and apply this knowledge in practice in the specialised computer laboratories.
Teaching hours may fall between 9am and 9pm, depending on your elective courses and tutorials.
Class sizes
Lectures are usually attended by larger groups and seminars/tutorials by smaller groups. This can vary more widely for modules that are shared between degrees.
Independent learning
Outside of timetabled sessions, you'll need to dedicate time to self-study to complete coursework, and prepare for presentations and exams. Our Drill Hall library and online resources will support your further reading and research.
You can also join a range of student societies, including our Computer and Technology Society, Gre Cyber Sec, Forensic Science Society, and Games Development Society.
Overall workload
Your overall workload consists of lectures, tutorials, labs, independent learning, and assessments. For full-time students, the workload should be roughly equivalent to a full-time job. For part-time students, this will reduce in proportion with the number of modules you are studying.
Assessment
On this course, students are assessed by coursework, examinations and a project. Some modules may also include 'practice' assessments, presentations, demonstrations, and reports, which help you to monitor progress and make continual improvement.
Feedback summary
We aim to give feedback on assignments within 15 working days.
Dates and timetables
The academic year runs from September to the end of August, as the students are working on their project full-time during the summer months.
Full teaching timetables are not usually available until term has started. For any queries, please call 020 8331 9000.
Fees and funding
Your time at university should be enjoyable, rewarding, and free of unnecessary stress. Planning your finances before you come to university can help to reduce financial concerns. We can offer advice on living costs and budgeting, as well as on awards, allowances and loans.
| Full time | Part time | Distance learning | |
|---|---|---|---|
| Home | £11,000 | £1,850 per 30 credits | N/A |
| International | £18,150 | £3,025 per 30 credits | N/A |
Accommodation costs
Whether you choose to live in halls of residence or rent privately, we can help you find what you're looking for. University accommodation is available from £126.35 per person per week (bills included), depending on your location and preferences. If you require more space or facilities, these options are available at a slightly higher cost.
Funding your study
There is a range of financial support options available to support your studies, including the Aspire@Greenwich award for study resources that many full-time students will receive.
EU students may be eligible for a bursary to support their study. View our EU bursary to find out more.
Discover more about grants, student loans, bursaries and scholarships. We also provide advice and support on budgeting, money management and financial hardship.
If there are any field trips, students may need to pay their own travel costs.
Careers and placements
What sort of careers do graduates pursue?
Graduates from the MSc Data Science and its Applications course are equipped for a career in Data Science and its applications or progress further in their field of choice.
Do you provide employability services?
Our services are designed to help you achieve your potential and support your transition towards a rewarding graduate career.
The Employability and Careers Service provides support when you are preparing to apply for placements and graduate roles. It includes CV clinics, mock interviews and employability skills workshops.
Each School also has its own Employability Officer, who works closely with the industry and will provide specific opportunities relevant to your own course.
More about Careers.
Support and advice
Academic skills and study support
We want you to make the most of your time with us. You can access study skills support through your tutor, lecturers, project supervisor, subject librarians, and our academic skills centre.
We provide additional support in Mathematics.
Support from the department
As a student in the School of Computing and Mathematical Science, you will be able to enter our Oracle mentoring scheme. This helps you liaise with industry for advice on careers, professional insight, job-hunting, and you'll also develop skills to boost your employability.
Not quite what you were looking for?
We've got plenty of other courses for you to choose from. Browse our postgraduate courses or check our related courses below.....
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