Data Science, MSc

University of GreenwichGreenwich, United Kingdom

Tuition Fee

GBP 18,700 / Per course

Start Date

Jan 1, 2027

Study Mode

On campus

Duration

12 months

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Program Details

Degree
Masters
Major
Artificial Intelligence | Data Science
Area of study
Information and Communication Technologies
Timing
Full time
Course Language
English

Intakes

Program start date
Jan 1, 2027
Sep 1, 2027

Program Overview

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
---|---|---|---
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


MSc in Data Science - University of Greenwich


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.

Outline:


Full-time:


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)

Part-time:


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

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)

Assessment:

The program utilizes a variety of assessment methods, including:

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

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.

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.


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.

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.

About University

University of Greenwich: A Summary


Overview:

The University of Greenwich is a public university located in London and Kent, England. It boasts three campuses: Greenwich, Avery Hill, and Medway. The university is known for its diverse student body, with students from over 150 countries, and its commitment to providing a high-quality student experience.


Services Offered:

The University of Greenwich offers a wide range of services to its students, including:

    Accommodation:

    On-campus accommodation options are available at all three campuses.

    Careers:

    The university provides career guidance and support services to help students find employment after graduation.

    Student Support:

    A variety of support services are available to students, including academic advising, counseling, and disability support.

    Financial Aid:

    Scholarships and bursaries are available to help students finance their studies.

    Digital Student Centre:

    A digital platform offering support for new and returning students.

Student Life and Campus Experience:

The University of Greenwich offers a vibrant and diverse campus experience. Students can expect:

    Lively Students' Union:

    Each campus has a Students' Union that organizes social events, clubs, and societies.

    Modern Facilities:

    The university has invested in modern facilities, including libraries, labs, and sports centers.

    Excellent Transport Links:

    All campuses are easily accessible by public transport, with connections to central London.

    Campus Bus Service:

    A bus service connects the three campuses.

Key Reasons to Study There:

    Award-Winning Research:

    The university is recognized for its high-quality research, which has won numerous awards.

    Gold in the Teaching Excellence Framework (TEF):

    This recognition highlights the university's commitment to providing an outstanding student experience.

    Diverse Community:

    The university welcomes students from all over the world, creating a diverse and inclusive learning environment.

    Flexible Learning Options:

    The university offers a range of flexible learning options, including online and part-time study.

    Strong Graduate Prospects:

    The university has a strong track record of graduate employment, with many graduates going on to successful careers.

Academic Programs:

The University of Greenwich offers a wide range of undergraduate and postgraduate programs across various disciplines. Some of the key academic strengths include:

    Business and Management:

    The university is known for its strong business programs, including MBA and MSc programs.

    Engineering and Technology:

    The university offers a range of engineering and technology programs, including civil engineering, mechanical engineering, and computer science.

    Arts and Humanities:

    The university has a strong reputation in the arts and humanities, with programs in English literature, history, and creative writing.

    Health and Social Care:

    The university offers a range of health and social care programs, including nursing, social work, and psychology.

Other:

  • The university has a strong commitment to sustainability and has launched a university-wide transformation for a Greener future.
  • The university is home to the Greenwich Portraits series, which celebrates the diverse journeys of its students and alumni.

  • Student Life and Campus Experience:

    While the context mentions the Students' Union and facilities, it does not provide detailed information on student life and campus experiences.

  • Key Reasons to Study There:

    The context mentions some advantages, but it does not explicitly highlight the key reasons to study at the University of Greenwich.
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