The Data Lab Academy (TDL) Programme Funding Call for 2024-25
Scottish Universities are invited to apply to become part of The Data Lab Academy programme for AY 24-25 providing the opportunity for their students to receive scholarships to fund their MSc studies.  These students will also join a programme of employability, networking and skills training which complements their academic studies, improves opportunities and better prepares them for the fast-paced and changing world of work. The programme is funded by The Scottish Funding Council. 

Background
 The Data Lab Academy programme differs from other academic courses as it focuses on applying academic knowledge to the world of industry, and on developing non-technical skills that are essential to becoming a data professional. Around 1,000 students have benefitted from the programme since AY 15-16 and we have worked with every university which provides data courses in Scotland over that period. You can view the list of approved The Data Lab Academy courses for AY 23-24 here.
 Students on our programme have access to our highly regarded employability enhancing, networking and skills programme which usually includes:  

• More than 50 hours of training spread across the academic year designed to maximise students’ employability and including the opportunity to apply to undertake a paid industrial placement in Scotland. 
• Access to networking events with industry experts and The Data Lab Academy partners. 
• An industry-sponsored, cohort-wide innovation challenge. 
• An interactive master class on Data Ethics. 
• Access to a network of expertise through The Data Lab MSc Alumni and The Data Lab Community. 
• Optional activities covering technical topics and exploring career routes. 

Apply to join the Programme
Scottish Universities are invited to apply to become part of The Data Lab Academy programme for AY 24-25 through our annual review process. We invite applications for MSc courses in data, AI and related subjects. Acknowledging that the demand for data engineering skills is high, we are keen to see new course applications from master’s courses in computer science and software engineering. However, we would also welcome applications for non-STEM courses which can demonstrate a strong data and/or AI element in their delivery. To be eligible to apply for The Data Lab Academy funded places, courses must be ready for delivery to commence in AY24-25.  Successful applications should demonstrate: 

• a strong focus on data science, data engineering, AI, or software engineering/ computer science with data elements e.g. Databases, Machine Learning, Cloud Computing/Cloud Technologies, SQL, NoSQL, Python, R. Related courses eg data analytics, business analytics and STEM data orientated courses can also apply; 
• innovation and creativity in course delivery; 
• high standards and the teaching of data ethics with responsible data science/AI embedded throughout the course; 
• a demonstrable commitment to maximizing diversity in applicants (examples of initiatives to reach out to underrepresented applicants); 
• strong industry engagement; and 
• willingness (for new courses) and evidence (for existing courses) of strong engagement with The Data Lab Academy programme and support of The Data Lab Academy placement programme. 

You can read more about programme here. 

The course review and allocation process will remain the same as in previous years, with successful universities awarded scholarship numbers to select the best candidates for their course. We will prioritise courses which clearly meet The Data Lab Academy application criteria and provide strong evidence of industry relevance and demand for the skills being taught. Where your university offers a suite of courses with shared core content, please submit one application eg MSc AI and MSc AI with Big Data should be considered, for the application process, as a single course with specialisms.  

We will continue to ask that potential scholarship candidates identified by universities are required to complete a short application form for review and approval by The Data Lab Academy prior to scholarships being confirmed with students. This is to ensure that all successful applicants to the programme are committed to its aims and are best placed to maximise the opportunity, including the placement option. Although we will prioritise courses which have a Trimester 1 start date, courses commending in Trimester 2 will also be considered.   

Funding available
Around 75 scholarships will support £6500 per student to cover MSc course tuition fees for The Data Lab approved courses for AY 24-25. We are pleased to be able to increase the level of the scholarship by 8% this year.  Any shortfall between the University’s tuition fee and the £6500 scholarship must be met by the University, and not by the student or any other third party.   

Student Eligibility
Only students who meet the SFC eligibility criteria can be considered for a scholarship. Refer to this SAAS advice (Eligibility Section) for guidance on who is eligible.   Universities are responsible for ensuring that any student referred for The Data Lab Academy scholarship meets the SFC criteria and can demonstrate the right to live and work (RTLW) in the UK.   

If funding becomes available, we may be able to support undergraduate integrated masters students and MSc students who do not meet the SFC eligibility onto TDL Academy programme.  We will send an update with criteria and instructions on how to apply for any additional places later in the year.   

Next steps

• Apply using this form. 
• The closing date for applications is 24 January 2024 at 23:59
• Universities will be notified on the success or otherwise of their application w/b Monday 5 February 2024  
• The Data Lab can offer marketing assistance to promote courses that join our programme. 

Need to know more? 

If you would like to discuss the Call requirements, and/or find out more about The Data Lab Academy programme, just let us know and we can schedule a meeting. Please note that TDL office will be closed over the Christmas period from Friday 22 December to Friday 5th January.   Contact us at tdl_academy@thedatalab.com 

TO BE ELIGIBLE TO APPLY FOR THIS SCHOLARSHIP YOU MUST BE REFERRED BY THE UNIVERSITY/COURSE WHERE YOU INTEND TO STUDY.   

Through our highly regarded and well established The Data Lab Academy, The Data Lab supports MSc students on a programme which focuses on applying academic knowledge to the world of industry, and developing the non-technical skills that are essential to becoming a data scientist. The Data Lab Academy Scholarship includes:
 

• A fully funded scholarship to cover tuition fees on an approved The Data Lab Academy course at a The Data Lab  partner university
• Sector-specific training in employability and communication skills*
• Access to networking events including Data Talent and a launch and closing event with presentations from industry experts, data scientists and The Data Lab Alumni and a Lunch & Learn programme throughout the year*
• The opportunity to apply to undertake a paid industrial placement in Scotland
• An industry sponsored innovation challenge*
• Membership of The Data Lab Community with access to a network of expertise, mentoring and a jobs board*
• Membership of The Data Lab Academy Alumni LinkedIn group
• A Masterclass on Data Ethics and Responsible Innovation*

*Core elements that must be completed by all The Data Lab Academy students (the time commitment is approximately 9 working days over a 12 month period).  See https://thedatalab.com/students/the-data-lab-academy/ for more details.

You have been recommended by a The Data Lab’s university partner for consideration by The Data Lab team for one of these scholarships. For us to make a decision on whether you meet our criteria, please complete the following form which asks for some information on you, and why you think you should be the recipient of one of our highly sought after scholarships.

The Data Lab Student Privacy Document sets out how The Data Lab will use the data you provide for the purpose of this application, including your rights under data protection law in relation to this personal information.  You can find the document here.