Hello again!

In this blog, I thought I would give two of the reasons why I developed and launched the UK’s first Level 3 diplomas in data science.

Data science is a discipline not a buzzword

Over the last decade or so, terms like “data science”, “artificial intelligence” and “machine learning” have become ubiquitous, often used by companies and the media to explain the benefits (and the dangers) of the latest advances from AI-led companies such as Google, Meta, OpenAI, and Tesla, to name a few.

However, data science is not just a buzzword, and it should not just be a term used by the sales and marketing departments of large data corporations for slick campaigns of their latest products and services.  Data science has become a true academic discipline distinct from the related fields of computer science, statistics, and mathematics.  Indeed, according to UCAS, for entry in 2023/2024 there are 478 data science undergraduate degrees in the UK provided by over 100 institutions.

When someone wants to study a particular subject at university (or college), regardless of whether that subject is mathematics, statistics, one of the sciences, or one of the arts, a person will almost always first study that subject at A-level, and use that qualification to meet entrance criteria set by the academic institution of their choice.  Our entire university entrance system is based on asking prospective students to obtain passes (at certain grades) in the particular subject of interest.

Therefore, if it is normal to study a subject at A-level before studying it at university, then why should this not also apply to data science?  With universities now offering first degrees in data science, it makes sense to me to offer people the chance to study it first at Level 3 (equivalent to A-level and International Baccalaureate) before asking them to commit to years of study at university. 

However, when I tried in 2021/22 to find a Level 3 data science course in the UK, I was astonished to discover no such course existed from any college or training provider!  This is what dared me to dream that I could establish and develop the UK’s first Level 3 diplomas in data science, and with the help of leading UK Awarding Bodies this is exactly what I did!

Lack of accreditation and professional development

During my 25+ year career, I have spent many years studying mathematics, statistics, and data science.

I have studied “formally” at various UK universities: the University of Glasgow, twice at the University of Warwick for two separate MScs, and the University of Oxford.  In addition, when I started my career, I initially trained to become an investment actuary with Mercer Investment Consulting, which involved studying over many years for recognised professional exams (https://actuaries.org.uk/).

I have also studied “informally”, taking countless short courses (or certifications) in programming, statistics, and data science, typically via Massive Open Online Courses (MOOCs), though also classroom-based courses delivered by various training providers.

When comparing and contrasting my own “formal” versus “informal” learning, for me there are several key disadvantages to studying informally:

• Informal learning (via a MOOC or via an unregulated training provider) is not accredited. At the end of such a course, students are simply awarded a “certificate of completion” issued by the training provider – students are not awarded an accredited diploma. This causes a major problem when trying to progress onto a UK or overseas university to study data science – universities do not recognise unaccredited certifications, i.e., it is not possible to use an unaccredited data science course to meet entrance requirements set by universities.
• With informal learning there is no clear professional development pathway. While achieving a “certificate of completion” does show an employer an aptitude for learning, if given a choice I believe most employers would prefer their employees to study an accredited course with a recognised syllabus, rather than a course of the employee’s own choosing with unknown academic value.

Of course, it has to be borne in mind that there are significant differences between studying a “formal” accredited course versus studying “informally”, including: the total study time and differences in costs.  That said, many providers of informal learning charge course fees which are commensurate with that of 1 year MSc courses, so a cost saving is not always guaranteed with “informal” learning.

With data scientists already playing critical roles across many sectors throughout our economy, and will do so much further in future, I believe it is critical to introduce minimum standards of education and training for the profession.

By introducing accredited Level 3 data science diplomas, I hope to address the problems caused by unaccredited courses, and hopefully it will pave the way for future professional training.

Conclusion

So, my top two reasons for developing the Level 3 diplomas in data science are:

• Data science is a field worthy of serious academic learning – it is not just a buzzword.
• The lack of accredited learning and professional development in data science is of concern.

I hope these reasons resonate with you.

If you have any questions about us or our diplomas, please email us at enquiries@delta-training.co.uk and we will get back to you as quickly as possible.

Until next time, take care.