MSc Data Science
Next event: 7 - 11 November 2022
Thinking of studying for a postgraduate degree at the University of Hertfordshire? Let’s Talk Postgrad is your chance to chat with our expert academics and learn more about your course of interest, life as a postgraduate student and the opportunities that further study will offer you.
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.
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.
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 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 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 application 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.
|Neural Networks and Machine Learning||30 Credits||Compulsory|
|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|
|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||Download|
|MSc Data Science||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.
You can also read our student blogs to find out about life at Herts.