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Data & AI Mastery

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Meet the Host

Dr Raoul-Gabriel Urma

Dr Raoul-Gabriel Urma is an EdTech entrepreneur, author, and international speaker focused on transforming workforce development through data and AI.

As the Founder and Chairman of Cambridge Spark, Raoul leads efforts to upskill employees of top organisations, including M&S and the BBC, with cutting-edge training. He co-invented the patented EDUKATE.AI platform, which personalises learning for data skills.

A member of YPO and affiliated lecturer at Cambridge, Raoul is also pursuing the Owner/President Management Program at Harvard. His best-selling book, Modern Java in Action, has sold over 60,000 copies, reflecting his impact on technology and education.

Latest episodes

Divya Kesavan on AI Transformation in Banking: Beyond RPA and Automation

Inside the Algorithm

Divya Kesavan on AI Transformation in Banking: Beyond RPA and Automation

In this episode, Divya walks Jeremy through the shift from rule-based RPA to reasoning-driven AI and why Lloyds' enterprise AI blueprint rests on three layers: reasoning, context and control. She unpacks what it actually takes to move an agentic system from a working proof of concept to a tool trusted with real banking decisions, including a striking example of an AI agent that went badly off script.

BlackRock CIO Simona Paravani-Mellinghoff on Data, AI and Financial Inclusion

Data & AI Mastery

BlackRock CIO Simona Paravani-Mellinghoff on Data, AI and Financial Inclusion

In this episode of Data & AI Mastery, host Dr Raoul-Gabriel Urma is joined by Simona Paravani-Mellinghoff, Chief Investment Officer at BlackRock, to explore why data quality and accessibility sit at the heart of every serious AI strategy.

Fast Enough to Matter, Careful Enough to Trust: How Leaders Are Governing AI

Data & AI Mastery

Fast Enough to Matter, Careful Enough to Trust: How Leaders Are Governing AI

In this episode, we bring together some of the sharpest thinking from across the show on AI strategy and governance: the decisions that happen before AI gets deployed and the frameworks that make sure it keeps working once it does.

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