Learn how Cambridge Spark helps organisations and leaders develop the data and AI skills that drive real transformation: cambridgespark.com

Ever wondered how Formula 1 teams make lightning-fast decisions at 200mph? In this episode, host Raoul-Gabriel Urma sits down with Ruth Buscombe, former race strategist for Scuderia Ferrari, Sauber, and Haas F1, to unpack the incredible world of real-time data strategy in one of the most high-pressure environments on Earth.

Ruth shares what it's really like making million-dollar calls in milliseconds, how her team processes 1.1 million data points per second from each car, and why the best lessons come from spectacular failures (not champagne-soaked victories).

One of the most fascinating parts of the discussion is when Ruth explains the eternal tension between data and gut feel, and why human intuition still matters even when you have the best models in the world.

Spoiler: your "gut" is really just your brain's LLM of past experience.

They also explore how F1 teams decide which sensors and data points actually move the needle when margins come down to 0.012 seconds, and what it's like to make high-stakes pit-stop calls with incomplete information (sound familiar, business leaders?).

Ruth also shares some powerful stories about ‘failing forward’, including why Mercedes boss Toto Wolff says "the day we fail is the day our competitors should fear us most."

Plus, they look at how AI is transforming sports broadcasting, with F1 now able to search 75 years of race footage using simple natural-language queries. And of course, they wrap up with a quick-fire round covering everything from Python vs MATLAB to favourite subjects at Cambridge and yes, Taylor Swift workout playlists.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

You can check out Formula 1's official site to learn more about the sport, or head to F1 TV if you want to dive deeper into the data and analysis Ruth works on.

Whether you're leading a startup, managing a data team, or just fascinated by how top performers think under pressure, this conversation is packed with insights you can actually use.

Chapters

00:00 - Introduction: Learning from F1's best failures

02:00 - Ruth's journey from Cambridge engineering to the F1 pit wall

03:00 - The insane scale of F1 data (1.1M points/second!)

06:00 - How do you decide what data to collect?

09:00 - Three pillars: Performance, competitor analysis & race strategy

13:00 - When should you trust data vs. gut instinct?

17:00 - Managing risk like a portfolio manager

20:00 - Creating a culture that embraces pressure

23:00 - AI transforming F1 broadcasting & fan experience

26:00 - Quick-fire: Python, physics & being a Swiftie

27:00 - Key takeaways for business leaders

Links

Connect with Ruth on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Visit Formula 1's official site at formula1.com

Visit F1 TV at f1tv.formula1.com

Learn how Cambridge Spark helps organisations and leaders develop the data and AI skills that drive real transformation: cambridgespark.com

In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma speaks with Ming Tang, Chief Data and Analytics Officer at NHS England. Ming has spent her career leading some of the most ambitious digital and data transformations in the UK public sector.

Together, they explore how data and AI are reshaping the future of healthcare, from modernising patient journeys and connecting siloed systems to deploying AI tools that help clinicians and operations teams work smarter. Ming’s insights highlight how the right mindset, structure, and curiosity can unlock meaningful impact at scale.

Listeners will also discover how the NHS is building a connected, patient-centric ecosystem through the Federated Data Platform (FDP) and the single patient record initiative and why listening and collaboration, not just technology, are key to solving complex system challenges.

Whether you work in healthcare, data science, or digital transformation, this conversation offers powerful lessons in leading with purpose, designing around users, and scaling innovation responsibly.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(03:30) Lessons from leading large-scale transformation

(06:00) Why listening and curiosity matter more than technology

(11:00) Designing flexible, modular NHS systems for efficiency and collaboration

(15:00) The Federated Data Platform: enabling connected, data-driven care

(18:00) Real-world AI applications in the NHS: discharge summaries, voice tech & analytics

(21:00) Advice for leaders; adopting AI through curiosity and context

(25:00) Raoul’s reflections; leading with empathy, curiosity, and user-first thinking

Useful Links:

Connect with Ming on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn more about how CambridgeSpark.com is helping organisations and professionals master Data & AI skills to stay ahead in the digital era.

In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Dr. Petar Veličković, Senior Staff Research Scientist at Google DeepMind and Affiliate Lecturer at the University of Cambridge.

Together they explore how cutting-edge AI research transitions from theory to practice, spanning from breakthroughs in graph neural networks that power Google Maps worldwide, to the use of AI as a discovery partner in mathematics. Petar shares his journey from Serbia to Cambridge to DeepMind, and the pivotal lessons learned at every stage.

Listeners will also hear how DeepMind’s graph machine learning models improve global travel-time predictions in Google Maps, how AI can accelerate scientific discovery, including mathematical proofs and what the concept of an “AI scientist” might mean for the future of research.

Whether you’re a data scientist, ML engineer, or executive exploring AI strategy, this episode offers a masterclass in applying AI innovation with purpose and impact.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(06:00) - Inside DeepMind; what a Senior Staff Research Scientist does

(13:00) - From research to real-world impact: challenges & latency trade-offs

(19:00) - AI for mathematics; collaborating with top researchers

(25:00) - Defining the “AI scientist” and the future of autonomous research

(30:00) - What’s next for AI agents and self-directed systems

(31:00) - Quick-fire round; programming languages, school favourites & music

(33:00) - Raoul’s takeaways; user focus, AI as a thought partner, safe deployment

Useful Links:

Connect with Petar on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn more about how CambridgeSpark.com is helping organisations and professionals master Data & AI skills to stay ahead in the digital era.

In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma, Founder of Cambridge Spark, sits down with Andy MacMillan, CEO at Alteryx, to explore how businesses can get real about data and make AI truly practical.

Andy shares how Alteryx helps people who understand data, but aren’t developers, build automations and AI-driven insights using messy, real-world data. He also offers a candid CEO’s perspective on what it really takes to make AI work at scale, from building AI alongside legacy systems, to designing responsible governance, to empowering every employee to use data effectively.

Andy also goes on to share how organisations can move fast and deliver value without waiting for the “perfect” infrastructure. He unpacks what agentic AI really means in the enterprise; how to give AI the right context and business logic to make accurate, trustworthy decisions and why hands-on leadership matters.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(02:00) – What is Alteryx and how it empowers non-developers

(08:00) – How CEOs can responsibly bring AI into the business

(15:00) – AI’s role in automation and pattern recognition

(24:00) – Responsible AI at Alteryx: Data clearinghouse model

(27:00) – Quick-fire round: Contrarian views, leadership, and learning

(33:00) – Raoul’s closing reflections and key takeaways

Useful Links:

Connect with Andy on LinkedIn

Visit the Alteryx Website

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Visit cambridgespark.com to explore how we help organisations upskill their workforce in Data & AI.

In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma speaks with Aidan Innes, Head of Data Standards at Nuffield Health, the UK’s largest healthcare charity.

Aidan shares his unique journey from sports science into data leadership, revealing how he built a strategy that connects patient outcomes, data literacy, and advanced analytics to drive both social and financial impact.

Elsewhere in the episode the pair discuss building outcome frameworks that scale across a complex healthcare organisation and how Nuffield Health is leveraging data apprenticeships to boost literacy, save millions, and empower staff.

Whether you’re a healthcare professional, a data leader, or simply someone passionate about how data drives impact, this episode is packed with insights and actionable takeaways.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(05:00) – COVID-19 rehabilitation programme and measuring outcomes

(08:00) – Scaling outcome frameworks across the organisation

(12:00) – Technology, governance, and people in data strategy

(16:00) – Measuring ROI and success stories in procurement

(18:00) – Advanced analytics and award-winning projects

(22:00) – Quick-fire round: contrarian views, learning habits, and personal insights

(24:00) – Aidan’s vision for the future of data in healthcare

(26:00) – Closing reflections and takeaways

Useful Links:

Connect with Aidan on LinkedIn

Visit the Nuffield Health Website

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Start your data & AI transformation journey with Cambridge Spark.

What does it take to prepare students—and their teachers—for a future shaped by AI? In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Prof. Sue Sentance, Director of the Raspberry Pi Computing Education Research Centre at the University of Cambridge, to explore the evolving landscape of computing education.

From the importance of teaching AI literacy and programming skills, to the challenges of teacher development and interdisciplinary learning, Sue offers research-backed insights into what inclusive, future-ready education should look like.

They discuss the role of pedagogy like PRIMM, frameworks such as SEAME, and why critical thinking—not just technical know-how—is essential for navigating today’s digital world. Whether you're an educator, policymaker, or AI enthusiast, this conversation will leave you rethinking how we equip the next generation with the skills to engage with, critique, and shape AI technologies.

Chapter Markers:

(00:00) Start Your Journey into AI Mastery

Kick off with Dr. Raoul-Gabriel Urma as he sets the stage for this episode's deep dive into computing education and AI literacy.

(01:20) Discover Prof. Sue Sentance’s Path to Shaping Computing Education

Explore Sue’s unique journey from AI PhD to classroom teacher to academic leader in computing pedagogy.

(03:29) Unpack the Latest Research in AI and Programming Education

Learn about Sue’s current work, including AI education, debugging, and longitudinal studies in physical computing.

(04:43) Master the Skills You Need in the Age of AI

Find out what essential skills students need today to thrive in an AI-driven world—and why confidence and critical thinking are key.

(08:51) Learn Why We Must Teach AI—and How to Do It Effectively

Sue explains why understanding AI isn't optional and offers insights on how we can teach it meaningfully in schools.

(11:59) Break Down AI Literacy with Real-World Frameworks

Get to grips with leading AI literacy models from UNESCO, OECD, and the EU—and their implications for education.

(15:01) Get Actionable Advice for Parents Navigating AI and Tech

Sue shares how parents can support their children in learning about AI—even without technical expertise.

(17:23) Explore the Line Between Teaching with AI and Teaching About It

Understand the difference and how educators can responsibly integrate AI tools into teaching practices.

(21:26) Debate the Future: Should We Still Teach Programming?

Sue tackles the hot topic of whether coding still matters in an age of generative AI—and what we risk if we stop.

(24:08) Hear Personal Insights in a Rapid-Fire Q&A

Find out Sue’s favourite programming language, subjects at school, and the music that fuels her work.

(28:23) Wrap Up with Final Thoughts on Empowering Learners with AI

Raoul reflects on key themes, from coding's long-term value to the role of education in fostering AI literacy.

Useful Links:

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Start your data & AI transformation journey with Cambridge Spark.

In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma speaks with Matthew Cloke, Chief Technology Officer at Endava, about how one of the world’s leading technology companies is embracing AI at scale.

Matt shares how Endava created an AI committee to set governance and strategy, built cross-functional champions networks and celebrated AI heroes to drive adoption, and invested in ChatGPT Enterprise across 8,000 employees, achieving 85–90% daily usage.

The pair also dive into the business case for AI and how to secure executive buy-in and why creating "wake-up moments" for executives is critical.

Whether you’re a senior leader shaping AI strategy or a professional curious about scaling adoption, this conversation is packed with actionable insights.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(03:45) Who owns the AI agenda? Inside Endava’s AI committee

(10:30) The Champions Network & AI Heroes

(15:20) Making the business case for ChatGPT Enterprise

(25:30) “Wake up, crawl, walk, run”: driving executive aha moments

(29:30) Balancing wait-and-see vs. first-mover advantage

(32:40) Quickfire round: contrarian views, environment, favourite language & more

(38:40) Closing reflections & key takeaways

Useful Links:

Connect with Matthew on LinkedIn

Visit the Endava Website

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com

Learn more about Cambridge Spark and how we’re helping organisations upskill their workforce in Data & AI: https://cambridgespark.com

In this episode of Data & AI Mastery, Dr. Raoul-Gabriel Urma sits down with Tamar Yehoshua, Advisor and former President of Product & Technology at Glean, and former Chief Product Officer at Slack and VP at Google. Tamar brings decades of experience leading product and engineering teams at the most influential tech companies.

Throughout this episode you will learn what AI literacy looks like in the boardroom today and why imagination, not just infrastructure, is the biggest barrier to AI transformation. You will also hear Tamar give us her take on the evolving role of AI agents in reshaping work across engineering, sales, and product and how the next generation of leaders can bridge the gap between incremental improvement and radical reimagination.

You’ll also hear insights on how top companies are defining their AI metrics, the role of boards in demanding ROI from AI investments, and why the most successful leaders are those who remain authentic, transparent, and consistent.

If you’re navigating AI transformation or leading teams through change, this is a conversation you won’t want to miss.

Chapter Markers:

(03:45) Tamar's leadership principles

(11:44) What metrics matter for AI?

(16:28) Use cases and real-world AI agent examples

(19:06) What is Glean and how does it work?

(25:52) From incremental improvement to reimagination

(28:54) Quickfire round: Lisp, math, musicals

(29:36) Closing reflections & key takeaways

Useful Links:

Connect with Tamar on LinkedIn

Visit the Glean Website

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programs at cambridgespark.com