Remove duplicate H2 headings from all markdown includes

- Removed H2 headings that duplicate YAML unit titles across all unit markdown files
- This prevents duplicate title display in published Learn content
- Maintains proper content structure while eliminating redundant headings

Author: staleycyn

learn-pr/wwl-azure/design-ai-workloads/includes/10-summary.md

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-## Summary and resources
-
 This module walks you through how to design and run Azure AI workloads by choosing the right blend of SaaS, PaaS, and IaaS services. The content focused on aligning AI solutions with business goals, skills, and governance, while applying security, operations, and responsible AI best practices.
 
 ### Key takeaways

learn-pr/wwl-azure/design-ai-workloads/includes/2-strategy.md

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 In this unit, you focus on building an AI strategy. The first step is getting familiar with the main types of AI solutions available in Azure—Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Once you understand these options, it becomes easier to choose the Azure AI solution that fits your organization’s needs.
 
 ### Adopt Microsoft software AI services (SaaS) for initial outcomes

learn-pr/wwl-azure/design-ai-workloads/includes/3-adoption-plan.md

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-## Plan for AI adoption
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 An [AI adoption plan](/azure/cloud-adoption-framework/scenarios/ai/plan) helps turn an AI strategy into real, actionable work. It keeps your AI projects aligned with business priorities, helps you think through the skills and resources you need, and makes it easier to plan timelines you can deliver on. 
 
 :::image type="content" source="../media/planning-steps.png" alt-text="Diagram of the planning steps discussed in the text.":::

learn-pr/wwl-azure/design-ai-workloads/includes/4-platform-workloads.md

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-## Design PaaS AI Workloads
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 When you're designing AI workloads on Azure PaaS, focus on three things: choose the right compute for generative AI, use the right services for traditional (nongenerative) AI, and secure networking to protect your data and manage access. Together, these considerations help ensure your AI solutions are scalable, secure, and aligned with your workload requirements.
 
 ### Select resources for generative AI

learn-pr/wwl-azure/design-ai-workloads/includes/5-infrastructure-workloads.md

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-## Design IaaS AI Workloads
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 An Azure landing zone is the recommended way to set up and manage your Azure IaaS environment at scale. It gives your organization a consistent foundation for deploying and operating workloads, including AI.
 
 You don’t need a separate 'AI landing zone' to get started. AI services can be deployed right alongside your other application workloads. From an Azure landing zone perspective, AI is just another workload. A workload that can be governed, secured, and managed with the same architecture, design principles, and tools your platform team already uses.

learn-pr/wwl-azure/design-ai-workloads/includes/6-governance.md

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-## Govern AI
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 Governing AI is about making sure your organization uses AI safely, responsibly, and in alignment with your existing risk, security, and privacy practices. 
 
 ### Apply AI principles

learn-pr/wwl-azure/design-ai-workloads/includes/7-secure-workloads.md

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-## Secure AI
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 When you build AI solutions in Azure, it’s important to [make security a priority](/azure/cloud-adoption-framework/scenarios/ai/secure) from the very beginning. AI systems create new attack surfaces that traditional security tools don’t fully cover. Follow these basic steps to get started.
 
 :::image type="content" source="../media/security-areas.png" alt-text="Diagram of the main security areas.":::

learn-pr/wwl-azure/design-ai-workloads/includes/8-manage.md

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-## Manage AI
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 Managing AI operations is about keeping your AI work consistent and reliable. Create an [AI Center of Excellence](/azure/cloud-adoption-framework/scenarios/ai/center-of-excellence) to guide strategy, choose the right framework (MLOps or GenAIOps), and standardize SDKs and APIs. Use sandboxes for safe experimentation and simplify tuning with tools like [Copilot Tuning.](/copilot/microsoft-365/copilot-tuning-overview) 
 
 > [!TIP]