Introduction to AI AGENT Testing Evaluation
Published 11/2025
Created by Dan Andrei Bucureanu
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 43 Lectures ( 3h 54m ) | Size: 2.8 GB
The intro course on how to test, measure, and improve AI agent behavior using modern evaluation tools
What you’ll learn
Understand the Fundamentals of AI Agent Testing
Design and Execute Systematic AI Agent Tests
Implement RAG (Retrieval-Augmented Generation) Evaluation
Understand Functional Testing of AI Agents
Understand Non-Functional Testing of AI Agents
Understand how to evaluate the Goal completion metrics
Understand how to evaluate the task completion metrics
Understand how to evaluate the plan creation metrics
Understand cost and efficiency evaluation
Compare Deterministic vs. Agentic vs. Autonomous Systems
Requirements
Will do learn
Curisity
Basic AI know how
Basic Testing Experience
Basic Software know how
no coding experience needed
Description
What You’ll LearnArtificial Intelligence agents are no longer static chatbots, they plan, reason, and act autonomously. This course teaches you how to systematically test, measure, and validate AI agent behavior using the latest tools and frameworks.Through real-world Python examples and structured exercises, you’ll learn how to evaluate both functional and non-functional aspects of AI systems; from goal completion and plan accuracy to efficiency and bias detection.By the end of this course, you’ll know how to design robust AI evaluation pipelines, implement RAG (Retrieval-Augmented Generation) tests, and confidently report metrics that reflect true agent performance.Course ModulesUnderstand the Fundamentals of AI Agent TestingLearn what makes AI agents unique — from autonomy and planning to tool-use and decision-making.Design and Execute Systematic AI Agent TestsBuild a repeatable test strategy using structured test cases, reproducible results, and automated evaluation scripts.Implement RAG (Retrieval-Augmented Generation) EvaluationEvaluate how effectively an agent retrieves and integrates external knowledge sources.Understand Functional Testing of AI AgentsTest accuracy, correctness, and behavior alignment with expected outcomes.Understand Non-Functional Testing of AI AgentsMeasure efficiency, robustness, reliability, and responsiveness in complex or dynamic environments.Evaluate Key Agent MetricsGoal CompletionTask ExecutionPlan CreationCost and EfficiencyCompare Deterministic vs. Agentic vs. Autonomous SystemsUnderstand the testing implications across AI system maturity levels.Tools & Frameworks Covered:DeepEval and GEval for metric-based evaluationRAGAS for assessing retrieval-based systemsPython for implementing automated test pipelinesBy the End of This Course, You Will Be Able To:Design a complete AI agent testing strategy from scratchImplement functional and non-functional AI validation frameworksApply objective metrics for task, goal, and efficiency evaluationTest RAG pipelines for retrieval and answer accuracyDistinguish between deterministic, agentic, and autonomous systemsBuild a portfolio project that demonstrates your AI testing expertise
Who this course is for
Software Testers & QA Engineers
AI / ML Engineers
Data Scientists & NLP Practitioners
AI Product Managers & Tech Leads
Quality Enthusiasts Curious About AI Testing
FINTRODUCTIONTOAIAGENTTETINGEVALUATION
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