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

• Aggregate agent performance data and apply statistical A/B tests
• Transform raw logs into actionable KPIs using SQL and dbt
• Design and execute controlled A/B experiments to compare agent versions

• Basic familiarity with topic and terminology
• Preparedness for applied exercises or case-based work