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Course Outline

Introduction to Microsoft Azure

  • Overview of Azure services and cloud computing fundamentals
  • Establishing an Azure subscription and configuration environment
  • Understanding resource groups, virtual machines, and networking components

Constructing Event-Driven and Serverless Architectures

  • Introduction to Azure Functions and serverless computing paradigms
  • Building event-driven applications using Azure Event Grid and Service Bus
  • Developing serverless APIs and automated workflows

Managing Storage and Databases in Azure

  • Exploring Azure Storage solutions (Blob, Table, Queue, File)
  • Administering Azure SQL Database and Cosmos DB
  • Integrating storage architectures into cloud applications

Deploying Web Applications in Azure

  • Understanding Azure App Service and various deployment models
  • Building and deploying containerized applications using Docker
  • Scaling web applications using Kubernetes and Azure Container Instances

Integrating AI and Machine Learning in Cloud Apps

  • Introduction to Azure AI and Cognitive Services
  • Utilizing Azure Machine Learning Studio for model development
  • Implementing computer vision and natural language processing features

DevOps and CI/CD in Azure

  • Establishing CI/CD pipelines using Azure DevOps
  • Managing infrastructure as code with Terraform and Bicep
  • Monitoring and logging applications using Azure Monitor

Enhancing Development with GitHub Copilot

  • Introduction to GitHub Copilot and AI-assisted coding tools
  • Using Copilot for writing, debugging, and optimizing cloud application code
  • Best practices for leveraging AI-assisted coding in cloud development

Capstone Project: Building an AI-Powered Cloud Application

  • Designing a scalable AI cloud solution
  • Developing and deploying the application
  • Optimizing performance, security, and monitoring

Summary and Next Steps

Requirements

  • Foundational understanding of cloud computing principles
  • Practical experience with at least one programming language (Python, JavaScript, or C# is preferred)
  • Familiarity with web application development and database management

Target Audience

  • Cloud developers and software engineers
  • AI specialists and data scientists interested in integrating cloud-based AI
  • IT professionals and DevOps engineers
 35 Hours

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