In this course, you will explore how Generative AI is revolutionizing cloud management by automating workflows, optimizing resource allocation, and enhancing overall efficiency. Whether you’re a Cloud Solutions Architect, DevOps Professional, or AI Enthusiast, this course will provide hands-on experience with Azure OpenAI, Microsoft Copilot, and other Azure services to streamline operations and reduce costs. Through real-world case studies, practical exercises, and expert insights, you’ll gain the skills needed to design, deploy, and manage AI-driven cloud solutions effectively.
This course is designed for Cloud Solutions Architects looking to optimize cloud resources with AI-driven strategies, as well as Data Engineers eager to apply Azure OpenAI for log analysis and anomaly detection. DevOps Professionals will benefit from learning how to integrate real-time AI-powered recommendations into their workflows, while AI Enthusiasts and Product Managers can explore Generative AI solutions within Azure to enhance automation and innovation. Whether you're aiming to improve cloud efficiency, streamline operations, or harness AI for real-time insights, this course will equip you with the skills to transform your cloud management approach.
To get the most out of this course, a basic understanding of cloud computing concepts and familiarity with Azure services will be helpful. While prior experience with Generative AI is not required, having some knowledge of scripting languages like Python will make it easier to follow along with hands-on exercises. Whether you're a cloud architect, data engineer, or AI enthusiast, a curiosity for AI-powered cloud optimization and a willingness to experiment with Azure OpenAI and Microsoft Copilot will set you up for success!
By the end of this course, you will have gained the knowledge and practical skills to leverage Generative AI in Azure for cloud optimization, automation, and real-time efficiency improvements. From deploying AI models with Azure OpenAI to utilizing Microsoft Copilot for smart recommendations, you are now equipped to transform your cloud operations with AI-driven strategies. But this is just the beginning—continue exploring, experimenting, and refining your skills to stay ahead in the rapidly evolving AI landscape.
In this course, you’ll explore the principles, strategies, and real-world applications of Generative AI in cloud management. Through hands-on experience with tools like Azure OpenAI, Microsoft Copilot, and other Azure services, you’ll learn to automate workflows, optimize resource allocation, and streamline operations. You’ll also evaluate cost-reduction opportunities and ethical considerations, ensuring secure and efficient AI integration in cloud environments.
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13 vidéos7 lectures1 devoir1 évaluation par les pairs
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13 vidéos•Total 72 minutes
Introduction and Welcome•3 minutes
Understanding GenAI and Why Azure?•4 minutes
Exploring Azure OpenAI Services •6 minutes
Understanding Model Selection and Use Cases•8 minutes
Configuring Azure OpenAI for Code Usage •7 minutes
Integrating Azure OpenAI into the DevOps Workflow •13 minutes
Utilizing Azure OpenAI’s GenAI for Log Analysis •6 minutes
Optimizing Resources and Managing Costs for AI Workloads •5 minutes
Finding Optimization Opportunities with Microsoft Copilot in Azure (Preview) •6 minutes
Implementing GenAI Optimization Opportunities for AI Workloads in Azure •4 minutes
Measuring Impact Before and After AI Optimization •5 minutes
Ensuring Long-Term Success with GenAI •5 minutes
Congratulations and Continuous Learning Journey•1 minute
7 lectures•Total 50 minutes
Welcome to the Course: Course Overview•5 minutes
Introducing to Responsible AI on Azure•5 minutes
Hands On Learning (HOL): Creating Your First Prompt Towards a Model with Azure OpenAI •10 minutes
Hands On Learning (HOL): Integrating Azure OpenAI into a Simple Azure Pipeline •10 minutes
Exploring Logging Architectures in Working with Azure OpenAI •5 minutes
Hands On Learning (HOL): Exploring Copilot Recommendations for Resource Optimization•10 minutes
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