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Master both sides of modern AI quality: use AI as an accountable assistant (testing with AI), and test AI-powered products with non-deterministic oracles, RAG checks, and safety gates (testing AI systems).
This course includes 50 hands-on labs — practice in real environments.
Haithem Mihoubi
Instructor
Free course
Enroll instantly — all lessons included
This course includes:
Master both sides of modern AI quality: use AI as an accountable assistant (testing with AI), and test AI-powered products with non-deterministic oracles, RAG checks, and safety gates (testing AI systems). This production-oriented phase combines written instruction, visual models, interactive decisions, and practical work on the shared QA Practice Hub application from manual testing through automation and SDET practices.
An LLM agent is a system that can execute tasks given in natural language or structured formats. It uses the planning capabilities of Large Language Models (LLMs) by calling tools that enable interaction with its environment. The agent also includes a memory mechanism. Both the agent's process and outcomes are non-deterministic.
LabsInspect, reproduce, and isolate failures across browsers, APIs, and distributed systems.
AI for QA
Free course
AI for QA walkthrough: AI tools for software quality (responsible use)
Using AI Responsibly
Limitations of AI
Human Validation
Privacy and Security
AI Evidence and Traceability
Prompt Engineering
Generating Test Cases
Generating Test Data
Bug Analysis
Log Analysis
Documentation Generation
Self Healing Locators
Visual AI Regression
AI Assisted Triage
Testing AI Systems
Non Deterministic Oracles
Prompt Regression
Evaluation Datasets
Model Evaluation
AI Output Quality
RAG Testing
Hallucination Detection
Adversarial Prompt Testing
Bias and Safety Testing
AI Agents for Quality Workflows
AI Governance
LLM Observability
AI in CI Quality Gates
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