MSc Data Science with Advanced Research
Why choose Herts?
- Teaching Excellence: You will be taught by internationally recognised research staff with expertise across mathematics, statistics, astrophysics, medical physics, and computer science (see key staff).
- Work-Placement Opportunities: You have an option to take a one-year paid industry placement. Students have had placements with organisations including NatWest, Sparta Global, and Sky.
- Industry Connections: Benefit from our strong links with the computing industry. We work with employers such as Microsoft and Hewlett Packard for students to engage in careers fairs and industry sessions.
Entry requirements and key information
For Near-STEM students, the normal entry requirements for the programme are a good (2:1 or above) Honours Degree (or equivalent) in a STEM subject (e.g. Mathematics, Engineering, Physical Sciences etc). If a student has a relevant STEM degree, then they will be considered ‘Near-STEM’. They will be offered the opportunity to participate in the Data Science Core Skills bootcamp but will not be required to participate/attend.
For Far-STEM students, the normal entry requirements for the programme are a good (2:1 or above) Honours Degree (or equivalent). The subject of the degree is not defined, since (a) many different, disparate subjects might have a Data Science relevance (e.g. Business, Geography), and (b) some students might possess a non- STEM degree but have relevant experience (e.g. from employment). For far-STEM students who do not possess a good Honours Degree or equivalent, applications will be assessed on a case-by-case basis. Applicants may be asked to submit a short portfolio providing evidence of:
- A basic level of numeracy (e.g. GCSE maths)
- Experience and competency with IT / software (e.g. use of Microsoft Excel)
- Experience of a basic interaction with data of any form (e.g. inputting values, making calculations, examining imaging, etc.)
School of study
School of Physics, Engineering and Computer Science
- Full Time, 2 Years
- University of Hertfordshire, Hatfield
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Upon completion of the programme you will be able to demonstrate (and apply) an understanding of a wide range of theoretical and practical skills enabling you to enter a variety of disciplines and industries. You will be able to:
- Understand and be able to critically assess the various strengths and weaknesses inherent to different data science methodologies
- Design creative strategies and solutions to tackle unfamiliar data science problems and critically assess outputs and results through appropriate statistically robust validation and other performance assessment techniques
- Effectively communicate problems, methods, results and conclusions through oral and written presentation to both expert and non-expert audiences
- Have an appreciation of both the underlying research behind data science techniques (e.g. cutting-edge algorithms and computational techniques) and their relevance and application across a broad range of disciplines.
About the course
Data is the currency of all but the most theoretically-based scientific research, and it also underpins our modern world, from the flow of data across international banking networks and the spread of memes across social networks, to the complex models of weather forecasting. The constant generation of data from our digital society feeds into our everyday lives, affecting how we receive healthcare to influencing our shopping habits. In order to handle, make sense of, and exploit large volumes of available data requires highly skilled human insight, analysis and visualisation. The professionals working in this field are called ‘data scientists’, who blend advanced mathematical and statistical skills with programming, database design, machine learning, modelling, simulation and innovative data visualisation. These professionals are in high demand in both public and private sectors in the UK and worldwide. This programme aims and learning outcomes are built around two guiding principles:
- To provide comprehensive understanding of the fundamental mathematical and statistical concepts underlying data science, and how they are implemented in algorithms and machine learning techniques to solve a variety of data processing and analysis problems.
- To provide training in the practical skills relevant to data science, central of which is the ability to write clean and efficient code in industry-recognised languages (in particular, Python and R), but also includes data handling, manipulation, mining and visualisation techniques.
Why choose this course?
- This programme is distinctive in its philosophy of widening participation and provides a route to gain skills and training in data science to those from a background not traditionally associated with the STEM-themes of mathematics, statistics and programming. The programme is designed to be appealing to a broad range of students who are seeking training or up-skilling in data science.
- You will benefit from the expertise of astrophysicists, physicists, mathematicians and computer scientists with international research profiles. Their day-to-day research involves application of, and in some cases the development of new, data science skills, from fundamental statistical analyses, the use of distributed high-performance computing, and research into novel artificial intelligence algorithms.
- We aim to make the programme distinctive in terms of the mixture of hard and soft skills, and the close personal relationship that we are developing with employers, which will feed into the programme through continuous assessment of the latest industry-relevant tools, which are continually evolving as new technology and software becomes available.
- You will experience a multidisciplinary approach to data science by experiencing challenges in computer science, creative arts, medical and business environments.
- You will have the opportunity to attend a wide range of research-focused seminars to excite and spark your intellectual curiosity.
- Computer Science saw 90% of its research ranked as world-leading (Research Excellence Framework, 2021).
What will I study?
The curriculum is structured to ensure are exposed to the fundamental mathematical and statistical principles underpinning all data science. These themes will always be relevant in what is a constantly evolving field. Theoretical work will be reinforced with practical application through hands-on laboratories and workshops, to enable you to understand and appreciate how fundamental principles are reflected in a broad range of data processing and analyses. You will become proficient in key practical skills (e.g. use of pandas for working with data structures within Python, and ggplot2 for visualisation in Python and R) using ‘real-world’ data where possible. In some cases, this data can be sourced from active research projects being conducted by members of the teaching staff.
The programme focuses on providing ‘end-to-end' training so that you become competent not only in the processing and analysis of data but also in manipulating and preparing data from a raw state as well as interpreting results and effectively communicating findings to others. This will enable you to be prepared for real-world challenges and applications and will help you to develop independence in your analytical and critical thinking. This will be nurtured in laboratory-based practical sessions so you can put your theories into practice.
Where will I study?
Learn in our brand-new School of Physics, Engineering and Computer Science building, opening in 2024, where you’ll experience a range of experiential learning zones.
The computer science labs are home to telecommunications, robotics and UX empathy labs, with a variety of research spaces that range from dark rooms to clean rooms, and sample prep labs to calibration and assembly labs.
You will also benefit from a Success and Skills Support Unit, which is aimed at helping you build your employability and academic skills. Plus, have access to industry mentors who will provide you with pastoral support, vocational guidance, and career progression opportunities.
The new building will also provide space to collaborate, with plenty of workshops, social and meeting spaces available. Even better, the building has been designed with the University’s net zero carbon target in mind, and forms part of our plan to replace or upgrade older sites that are energy inefficient.
|Multivariate Statistics||15 Credits||Optional|
|Linear Modelling||15 Credits||Optional|
|Foundations of Data Science||30 Credits||Compulsory|
|Applied Data Science 1||15 Credits||Compulsory|
|Applied Data Science 2||15 Credits||Compulsory|
|Data Science Project||60 Credits||Compulsory|
|Data Science Core Skills Bootcamp||0 Credits||Compulsory|
|Research Methods In Data Science||30 Credits||Compulsory|
|Advanced Research Topics in Data Science||30 Credits||Compulsory|
|Fundamentals of Data Science||30 Credits||Compulsory|
|Machine Learning and Neural Networks||30 Credits||Compulsory|
|Data Handling and Visualisation||15 Credits||Optional|
|Data Mining and Discovery||15 Credits||Optional|
Dr Ashley Spindler
Find out more about Dr Ashley Spindler
Dr Carolyn Deveraux
Find out more about Dr Carolyn Deveraux
Dr James Geach
Professor of Astrophysics / Programme Leader / Director of the Centre of Data Innovation Research
Find out more about Dr James Geach
Dr Ralf Napiwotzki
Find out more about Dr Ralf Napiwotzki
Dr Vidas Regelskis
Lecturer in Mathematics
Find out more about Dr Vidas Regelskis
Further course information
|Course fact sheets|
|MSc Data Science with Advanced Research||Download|
|MSc Data Science with Advanced Research||Download|
Sandwich placement or study abroad year
Applications open to international and EU students
At the University of Hertfordshire, we want to make sure your time studying with us is as stress-free and rewarding as possible. We offer a range of support services including; student wellbeing, academic support, accommodation and childcare to ensure that you make the most of your time at Herts and can focus on studying and having fun.
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Funding and fees
Other financial support
Find out more about other financial support available to UK and EU students
- £9900 for 2023/2024 and 2024/2025 inclusive
- £17950 for 2023/2024 and 2024/2025 inclusive
- £17950 for 2023/2024 and 2024/2025 inclusive
*Tuition fees are charged annually. The fees quoted above are for the specified year(s) only. Fees may be higher in future years, for both new and continuing students. Please see the University's Fees and Finance Policy (and in particular the section headed "When tuition fees change"), for further information about when and by how much the University may increase its fees for future years.
View detailed information about tuition fees
Living costs / accommodation
The University of Hertfordshire offers a great choice of student accommodation, on campus or nearby in the local area, to suit every student budget.
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How to apply
International/EU applicants without pre-settled status in the UK
Apply through our international/EU application portal
Home and EU applicants with pre-settled/settled status in the UK
Start Date End Date Link 26/09/2023 31/05/2024 Apply online (Full Time) 24/01/2024 31/01/2025 Apply online (Full Time)
Start Date End Date Link 26/09/2024 31/05/2025 Apply online (Full Time) 24/01/2025 31/01/2026 Apply online (Full Time)