AI Agent Evals and Reliability - Evaluations and Observability with Galileo AI
Master LLM Evaluations and Observability with Galileo AI
Created by Henry Habib
Get a practical understanding of how to evaluate and monitor large language models using Galileo AI. Build confidence in tracking, analyzing, and improving the reliability of your AI systems. Learn to apply observability techniques that help you make data-driven decisions for scalable AI projects.
Packt | Apr 2026 | 443 min
What You Will Learn
You will move from foundational concepts to hands-on practice, working directly with Galileo AI and related tools. Through guided activities, you will log model interactions, evaluate performance, and apply observability techniques to real-world data. Each step builds your ability to manage and improve LLM reliability.
Key Features
- Set up and use Galileo AI to monitor and evaluate LLM performance with confidence
- Log interactions, analyze agent graphs, and apply metrics to real-world AI scenarios
- Manage datasets and track model versions to support reliable, scalable AI systems
Target Audience
Designed for AI developers, machine learning engineers, and data scientists with some experience in AI or machine learning. If you want to deepen your skills in evaluating and monitoring LLMs, and you are comfortable with Python, you will gain practical tools and workflows to boost your AI projects.
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