Final Exam: IT Automation with Generative AI

Intermediate
  • 1 video | 32s
  • Includes Assessment
  • Earns a Badge
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Final Exam: IT Automation with Generative AI will test your knowledge and application of the topics presented throughout the IT Automation with Generative AI journey.

WHAT YOU WILL LEARN

  • Describe generative ai fundamentals and concepts, including how they can be applied on azure
    identify generative ai tools and libraries on azure and how they can be enabled to create and experiment with generative models
    integrate generative ai tools and libraries into azure-based workflows and applications
    identify generative ai techniques and how to apply them effectively using azure
    create, deploy, and manage generative ai models on azure, taking advantage of cloud resources for scalability and reliability
    diagnose and resolve issues related to generative ai models on azure cloud, ensuring reliable and smooth operation
    describe advanced generative ai techniques such as gans, vaes, and autoregressive models
    identify sre principles and practices that are used to ensure the reliability and availability of software systems
    describe generative ai and sre advancements with a focus on how azure based technologies can adapt and innovate in the space
    plan, deploy, and manage advanced generative ai solutions on azure improving sre workflows
    optimize and fine-tune advanced generative ai models effectively on azure, leveraging resources and tools for enhanced model performance and efficiency
    integrate generative ai models with existing sre tools on azure, enhancing incident management and monitoring processes
    describe ethical considerations and biases in ai, with a focus on their impact on responsible ai model development
    identify real-world implications of biased ai models, addressing their ethical and social consequences
    develop a responsible ai models, ensuring transparency, accountability, and ethical behavior
  • analyze ai models through an ethical lens, identifying potential biases and ethical concerns
    identify strategies to develop ai models that adhere to ethical standards, promoting fairness and ethical behavior
    identify the goals associated with each ai principle identified in the responsible ai standard
    identify the integration points of ai automation with it operations
    design ai automation workflows to enhance it operations efficiency
    describe how to use ai tools to automate it tasks and processes effectively
    showcase the integration of ai tools in it operations for effective automation
    discuss how to stay informed about the latest trends and advancements in ai automation in it operations
    develop strategies for continuous improvement in ai automation in it operations
    discuss ai-powered scripts for tasks like server monitoring and log analysis
    discuss ai-powered solutions for enhanced it support and sre operations
    describe how ai-powered scripts for improved performance and reliability in it tasks
    analyze the effectiveness of ai-powered scripts in solving it problems
    evaluate the impact of ai-powered solutions on it support and sre operations
    compare strategies for continuous improvement and learning in ai-powered it solutions

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