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Harnessing Generative AI: AWS & Azure for Business Leaders
Course Description
Overview
Generative AI is transforming how organizations innovate, optimize operations, and deliver value to customers. In this focused, one-hour webinar, business leaders will discover how to strategically leverage Generative AI solutions using AWS and Microsoft Azure. Explore core AI concepts, plan effective AI implementation strategies, understand key Azure and AWS generative AI services, and learn best practices for responsible and ethical AI deployment.Objectives
- Define Generative AI and recognize its strategic impact on business operations.
- Understand foundational AI concepts and how they apply to Azure and AWS platforms.
- Identify key Azure AI services, including Azure Cognitive Services, Azure OpenAI Service, Azure AI Foundry, and associated developer tools.
- Describe essential AWS generative AI offerings such as Amazon SageMaker, Amazon Bedrock, and Amazon Q.
- Recognize best practices for responsible AI, addressing issues of bias, transparency, and governance.
- Develop strategies for successful adoption and deployment of generative AI solutions in their organizations.
Audience
Topics
- Overview of today's session
- Brief Speaker Introduction
- What is Generative AI?
- Why Generative AI Matters Now for Business Leaders
- Common Business Use Cases and Strategic Value
- Introduction to AI
- Core concepts: Machine Learning, Deep Learning, Generative AI
- How AI is transforming industries today
- Azure AI Services Overview
- Key Azure AI services (e.g., Azure Cognitive Services, Azure OpenAI Service)
- Common business scenarios for Azure AI Services
- Introducing Azure AI Foundry
- Simplified AI development & deployment framework
- Examples of industry solutions built on Azure AI Foundry
- Azure Developer Tools and SDKs
- Azure AI Studio, Azure ML, APIs and SDKs
- How business leaders can leverage these tools for AI projects
- Key AWS services for Generative AI
- Amazon SageMaker: Building, training, and deploying AI models
- Amazon Bedrock: Foundation models for generative AI
- Amazon Q: Simplifying natural language queries
- Matching AWS services to business use cases
- Importance of Responsible AI: Bias, Fairness, Transparency
- Addressing potential risks: AI hallucinations, privacy, ethical considerations
- Executive considerations: Governance, skills gaps, ROI measurement
- Open session for participant questions
- Key takeaways & actionable next steps
- Resources and courses from LearnQuest
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