Prompt Optimization Tutorial (#1993)

This tutorial contains:
- Introduces a systematic, data-driven approach to prompt optimization
using NVIDIA metrics for efficient and robust evaluations.
- Demonstrates the process through a case study with a Diabetes
Medication Management Assistant, comparing standard and incentivized
prompts.
- Includes implementation steps for dataset preparation, evaluation
metric integration, and iterative improvement.

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Co-authored-by: Ani <5357586+anistark@users.noreply.github.com>

Author: sahusiddharth

docs/howtos/applications/index.md

@@ -10,6 +10,7 @@ usecases to solve problems you might encounter when you're building.
 - [Evaluating Multi-turn Conversations](evaluating_multi_turn_conversations.md)
 - [Estimate cost of evaluation](_cost.md)
 - [Evaluations with Vertex AI models](vertexai_x_ragas.md)
+- [Systematic Approach for Prompt Optimization](prompt_optimization)
 
 ## Testset Generation: