IT Automation with Generative AI

In the rapidly evolving landscape of information technology (IT), the integration of generative artificial intelligence (AI) is becoming increasingly essential. Generative AI, a branch of artificial intelligence, is responsible for generating content, such as text, images, and even code that is often indistinguishable from that created by humans. This course is designed to provide IT professionals with the knowledge and practical skills to leverage generative AI in the field of IT administration. Begin this course by exploring generative AI concepts and tools. You will learn how to deploy generative AI models and apply generative AI techniques on Azure. Then you will investigate how to create effective prompts and how to integrate your organization's data with Azure OpenAI models. Next, you will focus on analyzing generative AI models, automating tasks, and integrating generative AI tools. Finally, you will discover security concerns with using generative AI, find out how to apply security protocols, and troubleshoot generative AI. At the end of this course, you will be able to apply Generative AI models to address real-world IT administration challenges.

Unlock the transformative potential of advanced generative AI (GenAI) models in site reliability engineering (SRE). This course caters to SRE professionals, IT architects, and those eager to harness the full scope of generative AI in the context of SRE and covers the concepts of advanced generative AI techniques to bolster system reliability, scalability, and efficiency in SRE. In this course, we will begin with an overview of advanced GenAI and SRE. You'll explore how to deploy advanced models from the Azure AI model catalog and transition into testing approaches for applications integrating GenAI. Next, you'll deploy a GenAI-based application to Azure Kubernetes Service (AKS), explore the suitability of GenAI models for SRE, and see which SRE tools incorporate GenAI. With that foundation, you'll experiment with various methods for supporting SRE operations with GenAI including chatbots, implementing a backoff mechanism, evaluating model performance, and configuring log analytics for GenAI models on Azure. Lastly, you'll explore GenAI and SRE advancements, and fine-tune a GenAI model in Azure OpenAI Studio.

In a business environment where optimizing operational efficiency is pivotal, the integration of artificial intelligence (AI) automation stands out as a transformative approach to advancing IT operational frameworks. In this course, you will see how AI automation can be integrated with IT operations to design AI automation workflows that will enhance IT operations efficiency and automate IT tasks and processes effectively. Next, you will explore how IT automation can be evaluated and optimized using AI Tools and continuous improvement strategies. Finally, we will demonstrate the use of AI tools to integrate IT Operations.

Practical AI automation integration is not just a technological upgrade. It is a strategic enabler for enhanced system reliability, performance, and business continuity, allowing organizations to be more responsive and adaptive in a dynamic market landscape. In this course, you will see how AI-powered scripts can be used for enhanced IT support and site reliability engineering (SRE) operations, as well as tasks such as server monitoring and log analysis. Next, you will explore strategies for implementing secure and effective AI-powered IT solutions and evaluating their impact on IT support and SRE operations. You will also consider best practices for implementing secure and effective AI-powered IT solutions. Finally, you will discover how to optimize AI automation workflows for better performance in IT operations.

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.