While the amount of data being produced is proliferating at a staggering rate, the skills to extract information and the value we receive from it are both relatively scarce.
If you are looking to start a career in data science, or even further your current career, this course will provide you with vital skills required to develop your modelling and data handling expertise. You will gain a firm grounding in the principles of learning from data sets, whilst at the same time getting hands-on experience handling, analysing and visualising data. which will help you to realise your true potential while making you in demand in the modern workplace.
Both Artificial Intelligence and Analytical Reasoning are among the top three most-in demand hard skills (LinkedIn, 2019).
You can exit after 12 months with PgCert Data Analytics.
You can exit after 24 months with PgDip Data Analytics.
A first degree equivalent to a UK upper second class honours degree, normally with a substantial mathematics component (at least equivalent to Level-1 courses in Mathematics and Level-2 courses in Calculus and Linear Algebra at the University of Glasgow). Graduates who only have A-Level or Higher Mathematics, or equivalent, may also be admitted to the programme, however only subject to successfully completing an assessment of their mathematical skills before being admitted to the programme. Training material which prepares students for the assessment will be made available to applicants.
Graduates who achieved a degree classification equivalent to a UK lower second class honours degree, or similar, but who have substantial experience in a profession which involved a significant amount of programming, data management, data analysis or mathematical modelling might be also admitted to be programme. Such applicants might also be required to successfully complete an interview (as well as successfully completing the assessment of their mathematical skills, if required).
Previous study of Statistics or Computing Science is not required.
Distance and Flexible learning
College of Science and Engineering
School of Mathematics and Statistics