A complete guide to how to test AI Systems

📘 AI Evaluation Course Overview

A complete, hands-on course designed to help you evaluate AI systems — from measuring basic LLM outputs to building automated evaluation pipelines for production-grade, agentic applications.

🧭 Learning Path

🔹 Tier 1 — Foundations (Modules 01–03)

Build a strong base by understanding:

• What AI evaluation is
• Why it matters
• Key industry-standard metrics

🔹 Tier 2 — Core Skills (Modules 04–07)

Develop practical evaluation skills:

• LLM output evaluation
• Prompt evaluation techniques
• RAG pipeline assessment
• Safety and alignment checks

🔹 Tier 3 — Automation (Modules 08–11)

Move toward scalable systems:

• Use industry evaluation frameworks
• Build custom evaluators
• Curate high-quality datasets
• Integrate evaluation into CI/CD pipelines

🔹 Tier 4 — Advanced (Modules 12–14)

Handle complex AI systems:

• Multi-modal system evaluation
• Agentic workflow evaluation
• Statistical methods for rigorous analysis

🔹 Tier 5 — Application & Career (Modules 15–16)

Apply your knowledge in real scenarios:

• Build a complete evaluation pipeline
• Prepare for AI evaluation interviews

✅ Prerequisites

• Basic knowledge of Python
• Familiarity with LLMs (e.g., GPT, Claude, Gemini)
• Understanding of REST APIs
• (Optional) Familiarity with Azure services