Course summary
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.
Entry requirements
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.)
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Fees for Postgraduate Study 2023/24:
https://www.herts.ac.uk/study/fees-and-funding/fee-information/how-much-are-my-fees
Provider information
University of Hertfordshire
College Lane
Hatfield
AL10 9AB