Cohort Program

AI Evals For Engineers & PMs

Build, evaluate, and improve AI agents that work in production.

Categories: Generative AI

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Nathalia NelsonAI Educator | Practitioner

Limited-time: use code AAFPN for 30% off

Description

๐Ÿ† The most comprehensive AI evals course available. We've refined this material with over 4,500 engineers and PMs from teams like OpenAI, Google, Meta, Amazon, and Microsoft. Read what students say โ†’

Learning outcomes

  • Build an agent you can measure
  • Find what's broken with error analysis
  • Improve accuracy and cut cost with evidence

What's included

  • 2 live sessions

    Learn directly from Nathalia in real time, not from a recording.

  • Recording access

    Rewatch for 30 days after each session is delivered.

  • Office hours support

    Recurring group time to ask questions outside the sessions.

  • 1-on-1 feedback

    Personal review time on your own work.

  • Maram Guarantee

    Your purchase is backed by the Maram Guarantee.

Free resources

Not ready to buy? Start with something free from Nathalia.

Free resource

Build Your AI Moat: The Data Strategy Playbook for PMs

A practical playbook for product managers who want to turn their product's data into a durable competitive advantage. It walks you through how to identify the data assets you already have, where the gaps are, and how to build a strategy that compounds over time. Use it to align your team around a clear data vision and make sharper decisions about where AI fits in your roadmap.

Your AI Practitioner

Nathalia Nelson

AI Educator | Practitioner

An independent AI consultant and workshop facilitator based in London, with prior roles at BrightPath Learning Group and Northbridge Studio. She designs repeatable prompt systems, AI workflow playbooks, and adoption programmes for founders, consultants, and professional-services teams โ€” bridging the gap between emerging AI capabilities and everyday knowledge work. She has delivered live training across prompt engineering, generative AI, AI-assisted research, and responsible AI use, working effectively with both technical and non-technical audiences.

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