Data Science and AI Master’s degree conversion courses get funding boost

The University of Wolverhampton has secured additional funding to help deliver further scholarships for underrepresented students looking to study Data Science and Artificial Intelligence postgraduate courses.  

The grant funded scholarships, offered by the Office for Students (OfS), are worth £10,000 each, aimed at women, black students and disabled students, among other groups considered to be underrepresented in higher education. 

The University has secured an additional £40k to deliver four extra scholarships, increasing its total grant award funding from £720k to £760k, with the aim of delivering 71 scholarships by the end of March 2023. 

The courses are designed as conversion courses, so graduates of all ages who are looking to retrain, gain new skills or return to work after a career break can apply without needing a background in a STEM subject. Applications are welcomed from students with undergraduate degrees in subjects other than STEM, as well as for new graduates yet to enter the labour market.   

The University is one of 28 across England offering the courses which were introduced in June 2020 with the aim of responding to a skills shortage and a lack of diversity in the tech sector which is estimated to cost businesses £2 billion a year.  

The Office for Students (OfS) is the independent regulator for higher education in England.  

The University’s School of School of Engineering, Computing & Mathematical Sciences is committed to equipping students with the training, education and managerial soft skills required to meet the industry standards and code of practice in Artificial Intelligence and Data Science through the new course. 

Gea Perkins, 41 from Wolverhampton, is now studying for a Master’s degree in Data Science, funded by the OfS. She is studying part-time and has completed her first year of the course. Having secured a degree in 2001 in Business Administration and Marketing, Gea returned to studying 20 years later, having worked with data in a variety of roles throughout her career.  

She said: “Throughout much of my employment I have worked with data and could not get away from the fact that I enjoyed this element more than other areas. I have always been intrigued by the way in which data can be derived and analysed. I noticed over the last couple of years that there was an increase and need for more in depth timely data, and data requirements were becoming more complex.   

“When I saw the Data Science conversion course advertised with the University of Wolverhampton, I knew it was an excellent opportunity for me to develop the skills needed to meet the growing demand and gaps in the market. After reading articles about the low uptake of females in this area, I was inspired by those women who have progressed careers in data science, despite the sector mainly being male dominated.  

“I’m studying part-time, I work full-time and I have a family and this is the best option for me.  There’s lots of support from other students from different backgrounds it helps with learning.  I’m learning about a range of things, the background of data science and how companies can make decisions on the wealth of data they have.  This course gives you the tools, data visualisation, machine learning and research methods.  

“At my age I never thought I’d go back to University but there’s lots of support available and the course is fully funded which is a real advantage.” 

In partnership with the Department for Digital, Culture, Media and Sport (DCMS) and the Office for Artificial Intelligence (OAI), £13.5 million funding was allocated to the programme, consisting of £3.5 million to assist with course costs and £10 million to deliver 1,000 scholarships worth £10,000 each, aimed at women, black students and disabled students, among other groups considered to be underrepresented in higher education.   

The University was recently mentioned in the final report on the evaluation of National Data Skills pilot projects, written by the Careers Research & Advisory Centre (CRAC) who were commissioned as the independent evaluators of the project. 

ENDS