Cambridge Spark

Cambridge Spark Upskill your workforce with the data and AI specialists.

Cambridge Spark provides continuous professional development training for developers and data scientists. We offer intensive, part-time programmes, weekend bootcamps and regular community events on the latest tools and techniques in data science and software development, to equip individuals with the most relevant skills for industry needs. Cambridge Spark also runs specialised in-house training for corporate clients and teams looking to further develop their workforce.

As we celebrate 10 years of Cambridge Spark, we're proud to reflect on a year of industry recognition. This year, we cel...
06/08/2026

As we celebrate 10 years of Cambridge Spark, we're proud to reflect on a year of industry recognition.

This year, we celebrated three significant milestones:

🏆 Training Provider of the Year at the Apprenticeship & Training Awards.
📈 Recognised in the FT1000: Europe's Fastest Growing Companies for the fourth consecutive year.
🏅 Winners at the Quality Professionals Awards for Quality Improvement Initiative of the Year and Outstanding Contribution to Quality Improvement, alongside finalist recognition in two additional categories.

Awards are an important milestone, but the real achievement is what they represent: the hard work of our learners, the trust of our enterprise partners, and a team that continuously strives to deliver high-quality data and AI learning experiences.

Thank you to everyone who has been part of this journey. These recognitions belong to our learners, customers, partners and colleagues as much as they do to Cambridge Spark.

05/08/2026

Open-source models are catching up to frontier models fast and getting much cheaper while they do it.

That combination changes everything about how much AI actually gets used.

Alberto Romero, director of AI engineering at Aviva, thinks the industry isn't preparing for what comes next: a whole new order of scale.

As models become commoditised, more use cases become viable.

Add techniques like speculative decoding, which is speeding up response times significantly, and you get faster, cheaper, more instant AI everywhere.

His point isn't excitement for its own sake. It's a warning.

That level of utilisation and pe*******on only works if the foundations underneath it are solid.

Governance, standards, infrastructure – all of it needs to be built now, not scrambled together once demand has already arrived.

Watch the full conversation on what it takes to engineer AI at enterprise scale. Link in the comments.

To stay up-to-date with future episodes of Inside The Algorithm be sure to follow Data & AI Mastery wherever you get your podcasts

This August, Cambridge Spark marks 10 years🎉Over the past decade, we've had the privilege of working with learners, empl...
04/08/2026

This August, Cambridge Spark marks 10 years🎉

Over the past decade, we've had the privilege of working with learners, employers, partners and colleagues who believe, as we do, that investing in people creates lasting impact.

To begin our anniversary series, our founder, Dr. Raoul-Gabriel Urma, shares a few reflections on the past ten years and the people who have helped shape Cambridge Spark.

Thank you to everyone who has been part of our journey over the last decade. We're proud of what we've achieved together and look forward to continuing to build data and AI capability with organisations and individuals in the years ahead.

29/07/2026

Anthropic has just joined the FCA's second AI regulatory sandbox cohort.

This will give 21 firms access to Claude to explore agentic payments, fraud detection, compliance automation, and AI governance in financial services.

It is therefore a good moment to revisit something Edmund Towers from the FCA told us on Data & AI Mastery.

He spoke about how UK financial regulation actually works:

"The goal is clear, but how you get to that goal – there's a lot of freedom to innovate."

That's the whole premise of a regulatory sandbox in one line: outcome-focused rules, real room for firms to experiment with how they get there.

Worth remembering as AI moves from pilot to production across the sector.

🎧 Hear more from Edmund on the FCA's approach to AI and financial regulation. Link in the comments

In 2026, most organisations have more data than ever.But as teams look ahead to 2027, the real advantage will come from ...
27/07/2026

In 2026, most organisations have more data than ever.

But as teams look ahead to 2027, the real advantage will come from how well they can turn that data into faster decisions, clearer insight and measurable productivity gains.

That means reducing manual reporting.
Improving data confidence.
Building practical analysis skills across teams.
And helping employees move beyond spreadsheets into more valuable, evidence-led work.

Join our upcoming webinar, Data Analysis for Business Impact: Building the Skills Behind Smarter Decisions, hosted by Miran Mistry, to explore why data analysis is becoming a critical workforce capability.

Register now to save your place: https://eu1.hubs.ly/H0x9tPn0

What does practical AI capability look like in the workplace?Across our applied AI learning, learners identified 133 AI-...
23/07/2026

What does practical AI capability look like in the workplace?

Across our applied AI learning, learners identified 133 AI-enabled workflows spanning 38 employers.

From the 77 workflows with time-saving estimates that could be reliably quantified, the potential impact adds up to:

⏱️ 12,405 estimated hours saved annually
📅 The equivalent of approximately 517 days
📈 Or more than 1.4 years of continuous time
(And this is still a minimum estimate)

Behind every number is a learner identifying a real workplace challenge and applying AI to reduce repetitive tasks, improve consistency and create more time for higher-value work.

This is how practical AI skills translate into measurable organisational impact.

Ready to explore what applied AI learning could deliver for your teams?
👉 Book a discovery call with our team: https://eu1.hubs.ly/H0x6_pP0

22/07/2026

Technology. People. Process.

One guest. One clear answer to the question of what it actually takes to make AI governance work in practice.

In this special compilation episode of Data and AI Mastery, we bring together some of the most compelling moments from this year's conversations around a single theme: AI strategy and governance.

Sarah Self, at Aviva, breaks down what "guardrails" actually means once you move past the buzzword.

Not a policy bolted on at the end, but something architected in from day one, across the technology being built, the people using it, and the process wrapped around both.

Her team went as far as building their own platform rather than relying on off-the-shelf tools, specifically so those guardrails would be baked into every solution built on top of it.

This episode is available now on Apple Podcasts, Spotify and YouTube.

Links in the comments.

Be sure to subscribe to never miss a conversation with the leaders shaping the future of data and AI.

21/07/2026

“Software can be bought. Capability has to be built.”

In this clip from our recent webinar, Engineering AI Readiness, Miran Mistry explains why technology is not the biggest barrier to AI success.

Organisations can adopt the latest AI platform, but trusted data, engineering expertise, responsible use and the culture to apply AI well take time to develop.

Maybe the better question is not just, “How do we implement AI?”
It is: “Have we built the capability to use AI well?”

Watch the full webinar on demand to explore how organisations can build the data and AI engineering skills needed to move from AI ambition to real-world implementation.

Watch on demand: https://eu1.hubs.ly/H0x2SQF0

✨ Alumni Spotlight: Great ideas don’t create impact until they’re put into practice. Adeyemi Sonubi’s journey shows how ...
17/07/2026

✨ Alumni Spotlight: Great ideas don’t create impact until they’re put into practice. Adeyemi Sonubi’s journey shows how combining deep technical expertise with practical AI skills can transform complex theory into real-world business solutions.

With a postgraduate background in Mathematical Finance, Adeyemi Sonubi, Model Validation Manager at Aviva Investors, began his career immersed in advanced research and mathematical modelling. However, he recognised that applying complex theories to practical business challenges required a different skill set. Through the AI & Data Science Apprenticeship, he bridged the gap between theory and practice, developing intelligent machine learning solutions that automate financial risk assessment. 🚀

Today, Adeyemi combines technical innovation with leadership, sharing his knowledge and mentoring the next generation of data professionals. 💡

👏 We’re proud to have Adeyemi in our learner community. His journey demonstrates that combining specialist expertise with practical learning can unlock innovation, leadership, and meaningful impact in data and AI.

👉 Thinking about advancing your career in data? Explore our AI Engineer Apprenticeship: https://eu1.hubs.ly/H0w_Twf0

16/07/2026

Apprenticeships have evolved far beyond traditional trades. Today, they offer organisations a powerful way to build Data and AI capability, develop existing talent and create lasting business impact.

Our Mid-Market Sales Director, Richard Lambden, joined Anthony Donovan, Learning Director at Donovan Training Associates Ltd, to challenge some of the misconceptions still surrounding apprenticeships and explore what effective workplace learning looks like in practice.

The conversation highlights the importance of employer support, blended learning and investing in people for the long term, not simply treating apprenticeships as a tick-box exercise.

Listen to the full conversation to explore how apprenticeships can strengthen workforce capability and support sustainable growth.

Link in the comments!

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