Data Science Education Centre of Excellence Strategy Group Remit
The Data Science Education Centre of Excellence (DSE CoE) is an entity which will provide leadership and coordination support in areas related to data science education and training for best practice and new initiatives by:
- Supporting proposers of ideas in converting opportunities into business plans that are workable given UoE structures
- Providing insight into existing capabilities and offerings to proposers
- Where appropriate, coordinate cross-University initiatives that can benefit from the networks established by the CoE.
Data science related education and training is a priority across the University. Our aim is to provide quality training delivered by experts in their field for a wide range of audiences – from school-aged children to individual college or university students; from PhD candidates to executives working in industry or government departments, including our own staff.
The Data Science Education Centre of Excellence (DSE CoE) will provide a focal point for data science related education and training activity. It is an entity which will provide coordination support for best practice and new initiatives across the University working with DDI Hubs / Skills Gateway and University Services. The DSE CoE Strategy Group will consist of representative members from the above groups and will aim to meet every two months beginning July 2019.
The DSE CoE itself will not deliver educational offerings but will leverage existing activities and programmes to ensure a consistent approach to data science related education and training, including, data skills development training, and data understanding across the University.
In line with the Mission Statement, the DSE CoE Strategy Group will:
1. Work to ensure a shared awareness of data science related education activities across the University including existing and proposed undergraduate and postgraduate curriculum, continued professional development and Executive Education training, MOOCs, outreach programmes, etc.
2. Identify common areas where improvements in services, policies, and/or procedures within the University could provide mutual benefit to be taken forward for collective discussion (this may be preliminary individual Hub/College benefits which may later provide benefits to additional Hubs/Colleges), using data science related education and training to pilot improvements, using the momentum behind data driven innovation targets to support this work.
3. Propose and recommend a priority list of projects to be taken forward by the CoE, recommending initial stakeholders for workshops and working group involvement and suggested timelines, again using data science related education and training to pilot enhanced or new initiatives.