Gui Diaz-Berrio has led marketing measurement at companies spending €100M+ on advertising, including Kindred Group (Head of Marketing Analytics) and enterprise clients through Pinemarsh Consulting. He's built models from scratch and managed vendor relationships — both perspectives taught in this course.
Author of \"Data Analytics for Marketing with Python\" (Packt, 2024) — covering the practical frameworks taught in this course.
He's faced the challenges you're dealing with — messy data, skeptical CFOs, vendor black boxes, and the pressure to prove ROI with limited experimentation budget.
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Author of \"Data Analytics for Marketing with Python\" (Packt, 2024) — covering the practical frameworks taught in this course.
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The full 4-week cohort (starting May 2026) covers the complete stack:
Join the waitlist to get early access and priority enrollment for the May cohort of Marketing Science Bootcamp with Claude Code.
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Author of \"Data Analytics for Marketing with Python\" (Packt, 2024) — covering the practical frameworks taught in this course.
He's faced the challenges you're dealing with — messy data, skeptical CFOs, vendor black boxes, and the pressure to prove ROI with limited experimentation budget.
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His mentorship has helped various students build real-time products & careers in the Agentic AI PM space.
Whether you're a hobbyist or a professional looking to get a grasp on GenAI Product Management, feel free to join our channels for more such sessions
Aurimas Griciūnas is a recognized AI expert, LinkedIn Top Voice in AI, and the founder of SwirlAI. He previously served as Chief Product Officer at Neptune.ai where he worked closely with top ML teams to scale infrastructure, evaluation, and LLMOps practices across industries. With over a decade of experience at the intersection of data science, machine learning, and software engineering, Aurimas has led AI initiatives in both startups and enterprise environments. His mission is to bridge the gap between hype and reality by teaching engineers how to build systems that work in the real world. Students will benefit from his hands-on knowledge, technical depth, and product-first mindset - gained by solving actual engineering problems.
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