With Big Data becoming more prevalent in our work-places, we are excited to launch this flexible program bringing bite-sized training opportunities for different levels of expertise using ‘dip in and out’ options to suit full time workers who have less flexibility for more formal courses. This innovative data science training program will provide insight for data handlers as well as overviews for those more removed from the analysis pipelines needing more of a basic appreciation of how to operate in this increasingly complex work space.
Professor Rebecca Oakey from the School of Basic & Medical Biosciences
05 March 2021
Funding boost for data science training in health and bioscience
A training programme to facilitate the understanding of the data landscape in medicine has been funded by UK Research and Innovation (UKRI).
A training programme to facilitate the understanding of the data landscape in medicine has been funded by UK Research and Innovation (UKRI).
The funded programme ‘Enabling the big data revolution through skills training’ is led by Professor Rebecca Oakey from the School of Basic & Medical Biosciences in the Faculty of Life Sciences and Medicine. The training program is designed to upskill health care professionals, researchers and industry partners in big data analysis using flexible learning approaches.
The grant is part of the £5 million of data training programme funding made available by UKRI which will enable researchers at different starting levels and career stages to develop their skills and gain confidence in managing and analysing their big data. The goal of this initiative is to increase UK capacity in data management and analysis within the health and biosciences.
The King’s led programme, one of eight funded nationally, is aimed at medical practitioners, clinicians, researchers, industry partners and workers in the health sector. The courses will range from data exploration, integration and manipulation to more in-depth analyses via computational statistical and artificial intelligence (AI) based methods. The trainees will have the opportunity to participate in the assembly of computational pipelines to analyse data, and to bring to the table their own data for collaborative analyses.
The training programme has been designed around three pillars: Health Data Science exploring electronic data records (WS1); 'Omics harnessing genetics and molecular data collected in online databases (WS2); Artificial Intelligence focusing data image analysis and understanding AI through practical applications (WS3).
This programme should facilitate collaborative efforts in identifying and overcoming the barriers for effective integration and translation across disciplines.
The funded programmes by UKRI will upskill over 1,500 trainees across academia, industry and healthcare in diverse research areas through a combination of workshops and e-learning programmes.
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