Overview

Learn to leverage the power of Microsoft Azure’s Apps, Data and AI solutions to modernize and build intelligent apps focusing on internal business critical applications and external customer facing apps. In this workshop you will learn more about the impactful application of generative AI, which harnesses massive data that will be huge for businesses. You will also learn to make use of Azure Data services and cloud-native app building features provided by Azure Kubernetes Services, Cosmos DB and GitHub.

Modules

Introduction to AI Apps

In this module you will learn about Azure AI Services and principles of Responsible AI to support ethical, impactful AI development. You’ll learn to apply the Well-Architected Framework for building secure, scalable, and reliable solutions, and explore best practices in DevOps and Security to streamline operations and enhance protection across the development lifecycle.

DevOps with GitHub

This course guides you through the modern development lifecycle, from planning and development to testing, delivery, and security. You’ll explore tools like GitHub Copilot and GitHub Codespaces to boost coding efficiency, along with Microsoft Dev Box and Azure Dev CLI for streamlined development environments. The course also covers using Visual Studio and Visual Studio Code effectively, providing a complete toolkit for building, testing, operating, and securing applications.

Building and deploying apps on Azure

In this module you will learn about deploying and managing applications on Azure App Service and Azure Kubernetes Service (AKS). You’ll learn how to build, deploy, and scale web applications and containerized workloads, leveraging the flexibility and scalability of these Azure services to optimize performance and manage resources efficiently in the cloud.

Azure Database for PostgreSQL

In this module you will learn about Azure Database for PostgreSQL, focusing on its architecture, high availability, and essential features like geo-replication, scaling, security, and migration. You'll also explore how to leverage Generative AI with Azure Database for PostgreSQL - Flexible Server to build intelligent applications, ensuring robust performance and scalability for modern data solutions.

Azure SQL Database

In this module you will learn about a comprehensive introduction to Azure SQL Database, covering key aspects of deployment and compute models to suit various application needs. You'll learn about the Hyperscale service tier for scaling large databases and best practices to secure your data on Azure SQL Database, ensuring performance, flexibility, and security for your cloud-based applications.

Globally distributed databases

In this module you will learn about Azure Cosmos DB, a globally distributed, multi-model database service. You’ll learn the fundamentals of data modeling for efficient and scalable applications, along with best practices for partitioning to optimize performance and manage large datasets effectively. This foundation will help you leverage Cosmos DB for high availability and low-latency applications.

Azure Cosmos DB for MongoDB

In this module you will learn about the using Azure Cosmos DB for MongoDB, covering how to structure models and partitions for optimal performance. You'll also learn strategies for migrating existing MongoDB applications to Azure Cosmos DB and best practices for monitoring and managing your database to ensure reliability and efficiency.

Azure AI Services

This course offers an introduction to Azure AI services and large language models (LLMs), showcasing how to harness the power of AI within your applications. You’ll explore Azure AI Studio and its tools, including Translator, Speech, and Vision services for diverse language and visual needs, as well as Azure AI Language and Document Intelligence for advanced text analysis and document processing. This foundation equips you to build intelligent, adaptable solutions on the Azure platform.

Azure OpenAI Service

This course provides a deep dive into Azure OpenAI Service and Azure AI capabilities, covering model types, Provisioned Throughput Units (PTU) for scalability, and prompt engineering techniques. You'll gain an understanding of embeddings and Azure AI Search to enhance AI-driven search on your data. The course also emphasizes Content Safety and Responsible AI practices, ensuring secure and ethical AI deployment across applications.

Building optimized solutions with Well Architected Framework guidance

This course focuses on key principles for optimizing cloud solutions, including reliability, security, and cost optimization. You'll learn strategies for achieving operational excellence while enhancing performance efficiency across your services. By understanding these critical areas, you’ll be equipped to design and manage robust, secure, and cost-effective cloud environments that meet organizational goals.

Security

This course covers essential security tools and practices for managing cloud applications and services, starting with Azure Key Vault for secure key management. You’ll explore authentication and authorization using Entra ID, as well as leveraging AI Red Team Tools to test security measures. Additionally, the course delves into Defender for Cloud for safeguarding containers and app services, and introduces GitHub Dependabot for automating dependency updates, ensuring robust security across your development lifecycle.

Post-training Skills Assessment

Take this assessment to validate your skills gathered from the self-paced online learning completed in this course to mark your completion.

Course Completion Survey

Share your feedback with us regarding your experience!

Intermediate

  • Style

    Self paced

  • Target Audience

    Technical Project Ready

  • Certification Course

    No

  • Hands on Labs

    No
Solution Areas

Azure - Data and AI, Build and modernize AI Apps​

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