About This Course
Course Remade in June 2026 with latest Deep Evals Framework -- ~~Artificial Intelligence is rapidly transforming software applications, and traditional testing approaches are no longer enough to validate the quality of AI-powered systems. Whether you are working with AI Agents, Chatbots, Copilots, or Retrieval-Augmented Generation (RAG) applications, ensuring accuracy, reliability, safety, and performance has become a critical skill for modern QA and Engineering teams.In this course, you will learn how to systematically test and evaluate AI systems using DeepEval, one of the most powerful open-source frameworks designed specifically for AI evaluation. Starting from the fundamentals, you will build a strong understanding of AI testing concepts and gradually progress toward implementing real-world evaluation strategies used in production AI applications.Throughout the course, you will learn how to measure the quality of AI-generated responses using industry-standard evaluation metrics, create and manage Golden Datasets, perform trace-based analysis, validate AI agent workflows, and build custom evaluation metrics tailored to your business requirements. You will also explore G-Eval, component-level testing, multi-turn chatbot evaluations, and advanced techniques for assessing conversational AI systems.The course further dives into testing Retrieval-Augmented Generation (RAG) applications by evaluating retrieval quality, response relevance, context utilization, and factual correctness. In addition, you will learn how to generate synthetic test data, automate evaluation workflows, and perform AI safety testing to identify harmful, biased, or unsafe outputs before they impact users.By the end of this course, you will be able to design and implement comprehensive AI testing frameworks for AI Agents, Chatbots, and RAG applications using DeepEval. Whether you are a QA Engineer, Automation Tester, SDET, AI Engineer, Developer, or technology enthusiast, this course will equip you with practical, hands-on skills that are increasingly in demand as organizations adopt AI-powered solutions at scale.Join me on this journey and learn how modern AI systems are tested, evaluated, and validated in the real world.
What you'll learn:
- Understand the fundamentals of AI Testing and how it differs from traditional software testing approaches.
- Set up and use the DeepEval framework to evaluate AI Agents, Chatbots, and RAG (Retrieval-Augmented Generation) applications.
- Measure AI system quality using industry-standard evaluation metrics such as Answer Relevancy, Faithfulness, Precision, Recall, and G-Eval.
- Create and manage Golden Datasets to build reliable and repeatable AI evaluation pipelines.
- Perform trace-based and component-level testing to identify issues within AI agent workflows and reasoning chains.
- Build custom AI evaluation metrics tailored to real-world business and product requirements.
- Test multi-turn chatbot conversations and validate contextual understanding across complex interactions.
- Evaluate RAG applications by assessing retrieval quality, context utilization, response relevance, and factual correctness.
- Generate synthetic test data to improve AI evaluation coverage and reduce manual effort.
- Perform AI Safety Testing to detect harmful, biased, unsafe, or undesirable model outputs.
- Learn and apply Python for AI testing automation, with Python fundamentals covered as part of the course for beginners.