The era of deterministic testing is over. Whether you're coming from manual testing or traditional automation (Selenium, Cypress), this curriculum is designed to transform you into an AI Quality Engineer capable of validating the world's most complex LLM systems.
Traditional tools can't test AI reasoning. We focus on Semantic Validation, Adversarial Red Teaming, and Automated AI Evaluation—skills that are currently in high demand but low supply.
The Python-based "Unit Testing" framework for LLMs. Automate the measurement of Faithfulness, Relevancy, and Hallucination scores.
Advanced observability and debugging. Go beyond the surface to see the full execution trace of your AI's reasoning.
The industry standard for model evaluation and visualization. Track how changes in prompts affect your AI's performance over time.
Automatically detect vulnerabilities, bias, and ethical risks in your AI models through specialized adversarial scans.
Master the shift from Pass/Fail to evaluating intent and safety. Learn Red Teaming and how to break AI systems.
No more Selenium. Learn to build high-scale test harnesses using Python to talk directly to AI APIs.
Deep dive into Retrieval-Augmented Generation. Measure how accurately your AI uses external data.
The final frontier. Testing autonomous agents that use tools, execute code, and make real-world decisions.