MSc Data Science
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 undertake a placement of up to one year conditional on course requirements. Placements may be paid or unpaid depending on the employer organisation. With the support from the Career Service at Herts, and the departments own Careers Advisor, you will look for your preferred placement during your first year of studies. 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
The programme offers three award routes that you can choose to study:
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 that students 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.
Where will I study?
Learn in our new School of Physics, Engineering and Computer Science building (SPECS), 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 our Academic Support Hub, 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.
Spectra also provides 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.
Key staff
Dr Ashley Spindler
Senior Lecturer
Find out more about Dr Ashley Spindler
Dr Carolyn Devereux
Programme Leader and Principal Lecturer
Find out more about Dr Carolyn Devereux
Dr John Evans
Lecturer
Find out more about Dr John Evans
Dr Mykola Gordovskyy
Senior Lecturer
Find out more about Dr Mykola Gordovskyy
Dr Vidas Regelskis
Senior Lecturer
Find out more about Dr Vidas Regelskis
Dr William Alston
Senior Lecturer
Find out more about Dr William Alston
Further course information
| Course fact sheets | |
|---|---|
| MSc Data Science | Download |
| MSc Data Science | Download |
| Programme specifications | |
|---|---|
| MSc Data Science | Download |
| MSc Data Science | Download |
| Additional information | |
|---|---|
Sandwich placement or study abroad year |
n/a |
Applications open to international and EU students |
Yes |