Product Design

Evals for AI Products — from model.fit() to market.fit()

This learning plan covers the full landscape of evaluation for AI systems, moving from classical machine-learning diagnostics to the challenges of modern generative, agentic, multimodal, and enterprise-scale deployments. Learners progress through foundational metrics, LLM and agent evaluation, multimodal testing, domain-specific benchmarks, operational and safety assessments, and commercial ROI evaluation. By the end, participants can design rigorous eval suites that reflect scientific best practices, real-world constraints, and business outcomes. The course blends technical depth with practical workflows that are essential for trustworthy, high-impact AI products.