40577-G: Microsoft Cloud Workshop: Innovate and modernize apps with Data and AI Course Overview

40577-G: Microsoft Cloud Workshop: Innovate and modernize apps with Data and AI Course Overview

The 40577-G: Microsoft Cloud Workshop: Innovate and modernize apps with Data and AI course is designed to equip learners with the skills necessary to leverage advanced cloud-based solutions for app innovation and modernization using data and artificial intelligence (AI). Through a combination of whiteboard design sessions and hands-on labs, participants will delve into a customer case study and design a proof of concept solution that integrates Azure Machine Learning, Azure Functions, Cosmos DB, PostgreSQL, and Power BI. The course emphasizes predictive maintenance models, anomaly detection, event sourcing, and CQRS patterns, helping learners understand how to enrich applications with smart data insights and AI capabilities. This learning path is ideal for professionals looking to enhance their expertise in crafting cutting-edge cloud solutions that drive business transformation and efficiency.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 8 Hours)
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Course Prerequisites

Certainly! To ensure that participants are well-prepared and can gain the most from the 40577-G: Microsoft Cloud Workshop: Innovate and modernize apps with Data and AI course, the following prerequisites are recommended:


  • A basic understanding of cloud computing concepts, particularly within the Microsoft Azure ecosystem.
  • Familiarity with Azure services such as Azure Functions, Cosmos DB, Azure Machine Learning, and Power BI.
  • Experience with programming languages commonly used in data science and application development, like Python or C#.
  • Knowledge of database concepts and experience with SQL, particularly with PostgreSQL or similar relational database systems.
  • An understanding of machine learning concepts and how machine learning models are trained and deployed.
  • Familiarity with software architecture patterns such as event sourcing and Command Query Responsibility Segregation (CQRS).
  • Ability to navigate and use the Azure portal to create and manage resources.

These prerequisites are intended to provide a foundation for the course material and activities. Even if you are not fully proficient in all these areas, a willingness to learn and engage with the course content will help you succeed.


Target Audience for 40577-G: Microsoft Cloud Workshop: Innovate and modernize apps with Data and AI

The course 40577-G trains professionals in modernizing apps using Azure Data and AI services, focusing on practical and design skills.


  • Data Scientists
  • AI Developers
  • Azure Developers
  • Cloud Solutions Architects
  • DevOps Engineers
  • IT Professionals with a focus on cloud computing and data solutions
  • Application Engineers looking to implement AI features into existing applications
  • Technical Team Leads overseeing innovation projects
  • Software Engineers interested in data-driven application development
  • System Integrators specializing in cloud solutions
  • Business Intelligence Professionals seeking to leverage Azure for analytics and AI


Learning Objectives - What you will Learn in this 40577-G: Microsoft Cloud Workshop: Innovate and modernize apps with Data and AI?

Introduction to Learning Outcomes:

This course aims to provide a comprehensive understanding of how to integrate Data and AI capabilities in app modernization. Students will learn to deploy AI models and utilize Azure services for real-time analytics.

Learning Objectives and Outcomes:

  • Understand the challenges and requirements of modernizing applications with AI and data services through a customer case study.
  • Design a scalable, AI-infused proof of concept solution that addresses real-world business problems.
  • Gain hands-on experience deploying a simulated data environment using Azure to model industrial operations.
  • Learn to use Azure Machine Learning to develop, train, and deploy a predictive maintenance model.
  • Create and implement Azure Functions to process and route event telemetry data to Cosmos DB.
  • Integrate predictive maintenance insights into event streams to enhance telemetry data.
  • Apply automated anomaly detection to improve the accuracy and value of the telemetry data.
  • Practice transferring enhanced telemetry data to a PostgreSQL database for further analysis and storage.
  • Modernize application architectures with event sourcing and Command Query Responsibility Segregation (CQRS) patterns.
  • Develop skills to visualize and interpret operational data using Power BI for informed decision-making and reporting.