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 
• 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.

 

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.