Data Science Accelerator

The Data Science Accelerator is a fantastic development opportunity for public sector analysts wishing to develop their data science skills while also achieving real business outcomes for their organisation. This programme is delivered in partnership with The Data Lab.

Live online

Self-Directed
Free

None of these dates work for you?
Contact us to enquire about this course

Description

The Data Science Accelerator is a development opportunity for analytical staff that will help build your confidence and give you experience to explore a business challenge for your organisation using data.

To get a place on the accelerator, you first need to identify a data science project and complete an application form outlining your idea and the data required.  You can apply as an individual, or make a joint application with one other person.

If your application is successful and you are accepted on to the programme, you will work on your project 1 day a week for 12 weeks with the support of a mentor.  This is protected development time, agreed with your line manager.

During the accelerator you will further explore the business challenge with your mentor, try different approaches and potentially develop a prototype.  Prototypes developed in accelerator can be the first step towards a longer term solution for your organisation.

Data

Data must be the central consideration of your project and we will ask you about data you plan to use in the application form.  You must have permission to use and access the data before your project starts.

If your project proposes to process information which is personal or personal sensitive, as defined under Data Protection Legislation, you will need to have the permission of the Data Controller to process the data.  You will also need to have a Data Protection Impact Assessment or Privacy Impact Assessment in place by the start of the accelerator.

Who can apply?

Participation is open to staff employed directly by a producer of Official Statistics.  You should be in a role that needs a high degree of analytical skills or are employed in one of the analytical professions.  This includes analysts, statisticians, economists, operational researchers and social researchers, anyone working in digital analytics, data or information management, working as an archivist or in the geospatial profession.

You can apply as an individual or make a joint application with one other person.  Previous participants have told us that being part of a team on an accelerator means that their project progresses more quickly.  The commitment to release both staff would need to be agreed with the relevant line manager/s and senior manager/s.

We are also open to considering applications from other public bodies where there is capacity to support projects.  We may also consider applications where a public body partners with analytical team(s) in an Official Statistics producer body.

What software will I have access to?

You will be offered access to the analytical workbench which provides a secure environment with permission controlled virtual machines.  Here you can work with all types of data in a world-class data centre with high performance computing power.  Your mentor will also have access to the workbench so you can work together.

The analytical workbench has a wide range of data science tools including: Anaconda, Conda, Emacs, Git, Jupyter Core, Jupyter Notebook, PostGIS, PostgreSQL, Python, QGIS, R and RStudio and you can download other software should you need it.

How to apply

Upon registering above, you will be sent a further email containing the application form to your registered email address.  

Fees and funding

The Data Science Accelerator programme is funded by Scottish Government, Public Health Scotland, National Records of Scotland and Registers of Scotland.

Additional information

This programme is delivered annually in partnership with The Data Lab and is managed by Scottish Government, Public Health Scotland, National Records of Scotland and Registers of Scotland.

Back to top