Data & AI Mastery

Discover how Cambridge Spark helps leaders and teams build the data and AI skills needed to operate in high-stakes, real-world environments: cambridgespark.com In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by Andrew Feustel, former NASA astronaut, ISS Commander, and veteran of three space missions. Andrew has spent over two decades at NASA, flying on the Space Shuttle, leading missions aboard the International Space Station, and performing complex spacewalks to repair critical infrastructure like the Hubble Space Telescope. In this conversation, he shares a rare, human perspective on decision-making in the most extreme data environments imaginable: outer space. Together, they explore what space exploration can teach business and technology leaders about trust, automation, AI, and the limits of data-driven systems. Listeners will learn how astronauts rely on data, telemetry, and human judgment during high-risk missions, why data never perfectly matches reality, and why that matters in critical environments and why humans must remain in the loop when decisions carry irreversible consequences This episode offers powerful lessons for leaders navigating AI adoption, risk management, and decision-making, reminding us that technology is only as effective as the humans who design, trust, and use it. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (04:40) — Why data is central to every space mission (09:40) — Trust, automation, and critical systems in spaceflight (11:00) — Why we don’t fully trust autonomous systems (yet) (14:20) — Why AI is essential for space telescopes and discovery (16:40) — What makes NASA exceptional at preparing people (19:10) — How AI is already accelerating space innovation (20:30) — Automated rocket landings and decision systems (23:50) — Quick-fire round: unforgettable space memories (28:00) — Raoul’s reflections: trust, AI, and human-in-the-loop systems Useful Links: Connect with Andrew on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn how Cambridge Spark helps organisations build the data and AI skills needed to drive cultural and business transformation: cambridgespark.com In this special episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma is joined by three senior leaders from Capgemini: Claire Williams, Vice President for Analytics & AI in the Retail and CPG sector, leads global data and AI transformation for consumer health organisations.Arlene Carsley, Head of Workforce Transformation, focuses on building the culture, skills, and mindset needed for lasting change.Mansukh Mann, Managing Consultant in Workforce Transformation, works at the intersection of data, AI, and talent strategy to ensure technology and people move in sync. Together, they explore what true data and AI transformation look like in practice and why success depends as much on people and mindset as it does on technology. Listeners will discover why the urgency for AI transformation is being driven from the boardroom down and what that means for leaders, how to balance quick wins with long-term value, how to create momentum without losing strategic focus, why 70% of transformations fail, and how to avoid the common traps of poor sponsorship, misaligned metrics, and siloed thinking. This episode is packed with practical lessons for executives, transformation leaders, and data professionals looking to turn AI ambition into sustainable impact. Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode. Chapter Markers: (01:38) - What’s Driving the Urgency Behind AI Transformation? (08:49) - FOBO: Fear of Becoming Obsolete (12:05) - Leadership Upskilling with Cambridge Spark (17:12) - Why 70% of Transformations Fail (23:10) - Early Warning Signs Your Transformation Is Failing (25:55) - AI for AI’s Sake: A Recipe for Waste (29:50) - Why Skills, Safety and Experimentation Matter (34:55) - Balancing Quick Wins with Long-Term Goals (41:00) - One Piece of Advice for CEOs (45:40) - Raoul’s Closing Reflections Useful Links: Connect with Claire on LinkedIn Reach out to Arlene on LinkedIn Learn more from Mansukh on LinkedIn Follow Raoul for more AI insights on LinkedIn Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com Visit Capgemini’s website for more information

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

In this engaging discussion, Andy MacMillan, CEO of Alteryx, shares his journey from product management in major companies like Oracle and Salesforce to empowering non-developers to harness messy data. He reveals how to implement AI responsibly in organizations and the importance of creating AI alongside legacy systems. Andy also explains the concept of agentic AI, emphasizing context for accurate decision-making, and highlights how practical problem-solving can drive ROI, citing examples like McLaren’s use of race data.

Aidan Innes, Head of Data Standards at Nuffield Health, shares his intriguing journey from sports science to data leadership. He discusses building outcome frameworks that influence patient care and the impact of advanced analytics on healthcare. Aidan highlights the importance of data literacy, revealing how apprenticeships have helped Nuffield save millions and empower staff. He also speaks about scaling COVID-19 rehab programs and measuring ROI, offering practical insights into the future of data in healthcare.

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: Enjoying the Show? If you enjoyed this conversation, help us spread the word: Rate & Review on Apple PodcastsVisit Cambridge Spark to explore programmes that future-proof your data & AI skillsConnect with Dr. Raoul-Gabriel Urma on LinkedInConnect with Prof. Sue Sentance on LinkedInExplore Cambridge Spark’s AI upskilling programs at cambridgespark.com

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

Tamar Yehoshua, former President at Glean and seasoned leader with a rich background at Google and Slack, discusses the essence of AI literacy in today's boardrooms. She emphasizes that imagination is the biggest hurdle to AI transformation, not just infrastructure. Tamar shares insights on AI agents' roles in various sectors and how successful leaders maintain authenticity and transparency. Additionally, she highlights the importance of defining AI metrics and the role boards play in ensuring a strong ROI from AI investments.