Analyze Agent Performance: Build and Test
Analyze Agent Performance: Build and Test is an intermediate course for data analysts, ML engineers, and developers tasked with optimizing AI systems. In a world where agentic AI is increasingly common, it is not enough to build an agent—you must prove its effectiveness. This course equips you with the data-driven skills to measure, monitor, and improve AI agents built with frameworks like LangChain, Autogen, and CrewAI.
You will learn to transform raw, noisy logs into actionable KPIs by applying data aggregation techniques with SQL and dbt. Through hands-on labs, you will design and execute controlled A/B experiments, comparing agent versions to identify meaningful improvements. You will master core statistical methods, including the Chi-square test, to determine whether your results are statistically significant or just random chance. You will be able to move beyond correlation to causation, making objective, evidence-based recommendations on deploying agent enhancements.
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Agent Foundations
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
Agent cost bugs are debugging bugs
Dev.to AI
Agent Boosting: The Missing Workflow for Getting Real Results from AI Coding Agents
Dev.to AI
Building an Open-Source Consensus Protocol for Multi-Agent AI — Architecture Decisions and Trade-offs
Dev.to · Shyam Desigan
The 502 Bad Gateway Nightmare: Saving Your AI Applications with Asynchronous Queues
Medium · DevOps
🎓
Tutor Explanation
DeepCamp AI