🎤 Meet your instructor

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Sandro Hansen — 30 years in the water industry, from engineer to director, plus 6 years running his own consulting and engineering firm as an international consultant.

The turning point: realizing the industry was still solving problems he thought were already solved.

Today he builds the digital layer for water operations — helping plants run simpler, more fail-proof, and cheaper, with real peace of mind for the people running them.

Fluent in English, Spanish, and Portuguese.

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🎯 What you'll walk away with

By the end of the course, you'll be able to:

• ✅ Recognize where short-term digital value can actually be created
• ✅ Identify the operational data an AI use case actually needs
• ✅ Frame an AI project around measurable operational outcomes
• ✅ Tell a model that's ready to recommend apart from one that's ready to control
• ✅ Evaluate IoT, automation, optimization, and digital twin proposals with a critical eye

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What to expect

• A full-lifecycle decision framework for AI in water operations
• Conceptual literacy to work with a data science team — no code required
• An honest account of where soft sensors, predictive maintenance, and real-time optimization break down
• Field-based cases woven through every module </aside>

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What NOT to expect

• Code instructions
• Mandatory practicals or graded exercises
• Vendor or software comparisons
• MLOps deep-dive (drift, retraining, model ownership) </aside>

📋 Course structure — 10 modules, 5 live sessions

• 1st meeting — Data quality realities, what we're seeing in our own plants
• 2nd meeting — Where soft sensors succeed and fail in practice
• 3rd meeting — Optimization vs Control, where the line sits
• 4th meeting — LLMs and agents: appetite vs readiness in organizations
• 5th meeting — Open case review: student use case proposals