feat(evaluate): Add Azure AI Evaluation & Observability Workshop Notebook

[Govind Kamtamneni (thegovind)]

Description

This PR adds a comprehensive workshop notebook demonstrating Azure AI's evaluation and observability capabilities, developed in collaboration with Chang Liu (@changliu2) and Alex Sutton for TechConnect. This is the first iteration of the workshop material, which has been fully tested and provides hands-on examples of:

• Safety evaluation using ContentSafety, Violence, and HateUnfairness evaluators
• Security testing with DirectAttackSimulator and adversarial testing
• Quality assessment using Relevance, Coherence, and Groundedness evaluators
• Cloud-based evaluation workflows with azure-ai-projects
• Observability setup with OpenTelemetry and Application Insights
• Best practices for responsible AI governance

The workshop includes:

• A Jupyter notebook with detailed explanations and working code
• Sample evaluation test data in JSONL format
• Environment configuration templates

This serves as a practical guide for developers to implement comprehensive evaluation and monitoring in their Azure AI applications.

Checklist

• I have read the contribution guidelines
• I have coordinated with the docs team (mldocs@microsoft.com) if this PR deletes files or changes any file names or file extensions.
• This notebook or file is added to the CODEOWNERS file, pointing to the author or the author's team.