Data Science, MSc

Program Overview

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Data Science, MSc

Our MSc in Data Science equips graduates to embark on highly skilled careers in data science, artificial intelligence and machine learning.

This specialist Master's in Data Science provides a theoretical knowledge of data science alongside the practical skills that will help you prosper in the jobs market.

You'll be exposed to a broad range of topics such as data science, statistics, specialist programming, machine learning and data visualisation.

School

Computing and Mathematical Sciences

Location

Greenwich Campus

Duration

• 1 years full-time
• 2 years part-time

Start month

September; January

Home /international fees 2025/26

£11,325 /£18,700

What you should know about this course

• You will learn about many interesting topics in modern data science statistics, data visualisation, programming, machine learning, and data visualisation, plus application areas such as business intelligence.
• We will provide you with the necessary tools to understand the in-depth theory behind data science and artificial intelligence.
• Gain practical skills for careers within this specialised field.

About our MSc Data Science

Want to find out more about studying a Master's in Data Science at the University of Greenwich? Hear from the course leader, Dr Tatiana Simmonds.

What you will study

Full time

Part time

• Full time
• Part time

Year 1

Students are required to study the following compulsory modules.

• MSc Project (60 credits)
• Big Data (15 credits)
• Data Visualisation (15 credits)
• Machine Learning (15 credits)
• Programming Fundamentals for Data Science (15 credits)
• Ethics in Data Science (15 credits)
• Essential Professional and Academic Skills for Masters Students
• Statistical Methods for Time Series Analysis (15 credits)

Students are required to choose 15 credits from this list of options.

• Clouds, Grids and Virtualisation (15 credits)
• Blockchain for FinTech Applications (15 credits)

Students are required to choose 15 credits from this list of options.

• Technologies for Anti-Money Laundering and Financial Crime (15 credits)
• Graph and Modern Databases (15 credits)

Year 1

Students are required to study the following compulsory modules.

• Big Data (15 credits)
• Machine Learning (15 credits)
• Programming Fundamentals for Data Science (15 credits)
• Ethics in Data Science (15 credits)
• Essential Professional and Academic Skills for Masters Students

Year 2

Students are required to study the following compulsory modules.

• MSc Project (60 credits)
• Data Visualisation (15 credits)
• Statistical Methods for Time Series Analysis (15 credits)

Students are required to choose 15 credits from this list of options.

• Clouds, Grids and Virtualisation (15 credits)
• Blockchain for FinTech Applications (15 credits)

Students are required to choose 15 credits from this list of options.

• Technologies for Anti-Money Laundering and Financial Crime (15 credits)
• Graph and Modern Databases (15 credits)

Entry requirements

If you are a UK citizen or have permanent residency from outside the UK

UK citizens and permanent residents

An undergraduate (honours) degree at 2:2, or above, in Computing, Computer Science, AI, Data Science, Mathematics, Physics, Engineering, Statistics, IT or a relevant STEM subject.

Applicants without a degree that have substantial commercial/industrial experience including software development using modern programming languages and design may be considered.

Applicants with a degree in another discipline should consider MSc Data Science and its Applications, a specialist course designed for applicants from any background.

International entry requirements

The University of Greenwich accepts a broad range of international qualifications for admission to our courses.

For detailed information on the academic and English language requirements, please find your country in our directory.

Alternatively, please contact us at .

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 to put your knowledge into practice in our specialist 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 Stockwell Street 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 .

Fees and funding

University is a great investment in your future. English-domiciled graduate annual salaries were £10,500 more than non-graduates in 2023 - and the UK Government projects that 88% of new jobs by 2035 will be at graduate level.

(Source: DfE Graduate labour market statistics: 2023/DfE Labour market and skills projections: 2020 to 2035).

Cohort | Full time | Part time | Distance learning
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Home | £11,325 | £1,887 per 30 credits | N/A
International | £18,700 | £3,117 per 30 credits | N/A

Fees information

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.

Accommodation pages

Scholarships and bursaries

We offer a wide range of financial help including scholarships and bursaries.

The Greenwich Bursary

This bursary is worth £700 for new undergraduate students with a low household income, entering Year 0 or 1 who meet the eligibility criteria.

The Greenwich Bursary

EU Bursary

Following the UK's departure from the European Union, we are supporting new EU students by offering a substantial fee-reduction for studying.

The EU bursary

Financial support

We want your time at university to be enjoyable, rewarding, and free of unnecessary stress, so 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.

Funding your studies

If there are any field trips, students may need to pay their travel costs.

Careers and placements

What sort of careers do graduates pursue?

Graduates from this Data Science course are equipped for employment in industry, commerce or research with a proficiency in the key theoretical and practical areas of data science, including their application to modern artificial intelligence systems.

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.

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 Computing and Mathematical Science School student you can enter our Oracle mentoring scheme. This helps students to liaise with industry for advice on careers, professional insight, guidance in looking for jobs, and developing employability and presentation skills.

Program Outline

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MSc in Data Science - University of Greenwich

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Degree Overview:

The MSc in Data Science at the University of Greenwich equips graduates with the skills and knowledge necessary for successful careers in data science, artificial intelligence, and machine learning. This specialist Master's program provides a strong theoretical foundation in data science alongside practical skills highly sought after in the job market. The program covers a broad range of topics, including:

• Data science
• Statistics
• Specialist programming
• Machine learning
• Data visualization
The program is accredited by BCS, The Chartered Institute for IT, partially meeting the academic requirement for registration as a Chartered IT Professional.

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Outline:

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Full-time:

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Year 1:

• Compulsory Modules:
• MSc Project (60 credits)
• Big Data (15 credits)
• Data Visualisation (15 credits)
• Machine Learning (15 credits)
• Applied Machine Learning (15 credits)
• Programming Fundamentals for Data Science (15 credits)
• Essential Professional and Academic Skills for Masters Students
• Statistical Methods for Time Series Analysis (15 credits)
• Optional Modules (Choose 15 credits):
• Clouds, Grids and Virtualisation (15 credits)
• Blockchain for FinTech Applications (15 credits)
• Optional Modules (Choose 15 credits):
• Technologies for Anti-Money Laundering and Financial Crime (15 credits)
• Graph and Modern Databases (15 credits)

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Part-time:

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Year 1:

• Compulsory Modules:
• Big Data (15 credits)
• Machine Learning (15 credits)
• Applied Machine Learning (15 credits)
• Programming Fundamentals for Data Science (15 credits)
• Essential Professional and Academic Skills for Masters Students

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Year 2:

• Compulsory Modules:
• MSc Project (60 credits)
• Data Visualisation (15 credits)
• Statistical Methods for Time Series Analysis (15 credits)
• Optional Modules (Choose 15 credits):
• Clouds, Grids and Virtualisation (15 credits)
• Blockchain for FinTech Applications (15 credits)
• Optional Modules (Choose 15 credits):
• Technologies for Anti-Money Laundering and Financial Crime (15 credits)
• Graph and Modern Databases (15 credits)

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Assessment:

The program utilizes a variety of assessment methods, including:

• Coursework
• Examinations
• Project
Some modules may also include:
• Practice assessments
• Presentations
• Demonstrations
• Reports

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Teaching:

• Learning takes place through a combination of lectures, tutorials, and practical work in labs.
• Smaller group sessions allow for discussion and development of understanding of lecture topics.
• Specialist computer laboratories provide opportunities for practical application of knowledge.
• Teaching hours may fall between 9am and 9pm, depending on elective courses and tutorials.
• The teaching team includes academics and practitioners with experience in various aspects of Computer Science, including Big Data.
• The majority of the team holds a teaching qualification.

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Careers:

Graduates from the MSc in Data Science are well-prepared for employment in industry, commerce, or research. They gain proficiency in key theoretical and practical areas of data science, including their application to modern artificial intelligence systems.

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Other:

• The program is taught from within the School of Computing and Mathematical Sciences.
• Students can join a range of student societies, including the Computer and Technology Society, Gre Cyber Sec, Forensic Science Society, and Games Development Society.
• The program is available to overseas students.
• Students with professional qualifications and/or four years of full-time work experience may be considered for entry on an individual basis.
• Students may be eligible for exemptions from courses based on prior learning.
• The academic year runs from September to the end of August, with students working on their project full-time during the summer months.

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Home/international fees 2024/25: £11,000 / £18,150 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. EU students may be eligible for a bursary to support their study. Discover more about grants, student loans, bursaries and scholarships. We also provide advice and support on budgeting, money management and financial hardship. Financial support If there are any field trips, students may need to pay their travel costs.