Agent Evaluation on Databricks
This course teaches students how to systematically evaluate AI agents using MLflow's evaluation framework, addressing the unique challenges of non-deterministic AI systems that traditional software testing cannot handle. Students learn to implement various evaluation approaches including built-in judges for common criteria like correctness and safety, guideline judges for business-specific requirements, and custom judges for specialized needs. The course covers both offline evaluation using curated datasets and online production monitoring, with hands-on experience using MLflow's tracing capabilities to understand agent execution patterns and collect human feedback from different stakeholder types. Through practical demonstrations and labs, students develop skills in creating evaluation workflows that drive continuous quality improvements throughout the AI agent development lifecycle.
In this course, the content was developed for participants with these skills/knowledge/abilities:
• Intermediate Python programming experience
• Basic SQL knowledge for querying and creating functions
• Familiarity with Databricks Data Intelligence Platform
• Understanding of Unity Catalog concepts including catalogs and schemas
• Basic understanding of large language models (LLMs) and prompt engineering
• Basic knowledge of MLflow
Self-Paced
Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
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Databricks has a delivery method for wherever you are on your learning journey
Self-Paced
Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
Register nowInstructor-Led
Public and private courses taught by expert instructors across half-day to two-day courses
Register nowBlended Learning
Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase
Purchase nowSkills@Scale
Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

