Analyze Agent Performance: Build and Test
Key Takeaways
Builds and tests agentic AI systems using LangChain and LangGraph in 3 weeks
Original Description
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 External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Agent Foundations
View skill →Related Reads
📰
📰
📰
📰
Mininglamp Technology Officially Open-Sources Octo: A New-Generation Platform for Human-AI Agent Collaboration
Dev.to · Mininglamp
I sent 500 applications and blamed the machines
Medium · AI
Designing Drones That Refuse to Fail
Medium · Machine Learning
Why Most Enterprise AI Projects Fail (And How to Build a Winning AI Strategy)
Dev.to AI
🎓
Tutor Explanation
DeepCamp AI