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Introduction to Generative AI on Azure Cloud

Unleashing the Power of Azure for Advanced Generative AI Solutions


3 Days (3.5 hours per day)


Basic Level

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As per your team needs

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This intensive 3-day course is designed to equip participants with the knowledge and practical skills needed to implement Generative AI solutions on the Azure Cloud Platform. Throughout the course, participants will delve into the fundamentals of Generative AI, focusing on the implementation of the Retrieval Augmented Generative (RAG) model. By the end of the course, participants will be adept at setting up Azure environments, training and deploying RAG models, and integrating them with Azure OpenAI for real-world applications.

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  • Data scientists
  • Machine learning engineers
  • Developers interested in implementing Generative AI solutions on Azure platform
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  • Introduction to Generative AI
  • Evolution of Generative AI 
  • How Generative AI Differs from Other AI Technologies
  • Exploring the Generative AI Value Chain
  • Current Trends in Generative AI including ChatGPT
  • Demos to give broader perspective about Bard, ChatGPT, MidJourney and more
  • Overview of Azure services relevant to Generative AI
  • Setting up Azure account and accessing Azure Portal
  • Introduction to Azure Machine Learning service
  • Overview of RAG model architecture and components
  • Exploring use cases for RAG in natural language processing tasks
  • Creating Azure Machine Learning workspace
  • Provisioning compute resources for model training and deployment
  • Configuring Azure resources for data storage and management
  • Preprocessing data for RAG model training
  • Training RAG model using Azure Machine Learning service
  • Evaluating model performance and fine-tuning parameters
  • Overview of Azure OpenAI service
  • Working with Azure Playground 
  • Exploring Prompt Engineering with Azure Playground
    • Importance of Well-Defined Prompts in Generative AI
    • Strategies for Crafting Effective Prompts
  • Understanding integration options with Azure Machine Learning
  • Deploying RAG model as a web service using Azure Machine Learning
  • Configuring endpoint for model access and interaction
  • Testing RAG model integration with Azure OpenAI using sample queries
  • Hands-on project to implement a custom scenario using RAG model on Azure Cloud Platform
  • Q&A session and review of key concepts covered throughout the course
  • Conclusion and next steps for further exploration in Generative AI and Azure integration
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  • Basic understanding of machine learning concepts and natural language processing
  • Familiarity with cloud computing concepts (Azure experience is a plus but not required)


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