Introduction to AI AGENT Testing | Evaluation
Introduction to AI AGENT Testing | Evaluation
Last updated 11/2025
Duration: 3h 54m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 2.80 GB
Genre: eLearning | Language: English
Last updated 11/2025
Duration: 3h 54m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 2.80 GB
Genre: eLearning | Language: English
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 Learn
Artificial Intelligence agents are no longer static chatbots, they plan, reason, and act autonomously. This course teaches you how tosystematically test, measure, and validate AI agent behaviorusing the latest tools and frameworks.
Through real-world Python examples and structured exercises, you’ll learn how to evaluate bothfunctional and non-functional aspectsof AI systems; fromgoal completionandplan accuracytoefficiencyandbias 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 Modules
Understand 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 AgentsMeasureefficiency, robustness, reliability,andresponsivenessin complex or dynamic environments.
Evaluate Key Agent Metrics
Goal Completion
Task Execution
Plan Creation
Cost and Efficiency
Compare Deterministic vs. Agentic vs. Autonomous SystemsUnderstand the testing implications across AI system maturity levels.
Tools & Frameworks Covered:
DeepEvalandGEvalfor metric-based evaluation
RAGASfor assessing retrieval-based systems
Pythonfor implementing automated test pipelines
By the End of This Course, You Will Be Able To:
Design acomplete AI agent testing strategyfrom scratch
Implementfunctional and non-functional AI validationframeworks
Applyobjective metricsfor task, goal, and efficiency evaluation
TestRAG pipelinesfor retrieval and answer accuracy
Distinguish betweendeterministic, agentic, and autonomous systems
Build aportfolio projectthat 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
More Info