Azure Training in Gaia

This instructor-led, live training in Gaia (online or onsite) targets intermediate-level Java developers, software engineers, and cloud enthusiasts eager to harness the power of Azure OpenAI to create intelligent applications.

Upon completion of this training, participants will be capable of:

• Grasping the core principles of Generative AI and its practical applications.
• Provisioning and managing Azure OpenAI services.
• Integrating OpenAI models into Java-based applications.
• Deploying AI-driven features within web applications.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level cloud engineers and IT professionals who wish to use Terraform to automate the deployment, management, and scaling of infrastructure on the Azure cloud platform.

By the end of this training, participants will be able to:

• Understand the basics of Terraform and its benefits in infrastructure as code.
• Set up and configure Terraform for Azure.
• Develop, test, and deploy Terraform configuration files for various Azure services.
• Use Terraform for managing and scaling Azure resources.
• Implement best practices for Terraform state management and version control.
• Integrate Terraform with Azure DevOps for automated deployments.
• Create reusable Terraform modules for consistent resource provisioning.
• Utilize advanced features of Terraform for complex infrastructure deployments.

This instructor-led, live training in Gaia (online or onsite) is tailored for intermediate to advanced professionals seeking to build and deploy AI-driven cloud applications using Microsoft Azure.

Upon completion of this training, participants will be capable of:

• Constructing event-driven and serverless applications with Azure Functions.
• Administering Azure storage solutions and virtual machines.
• Deploying and scaling web applications via Azure App Service and Docker containers.
• Integrating AI, machine learning, and natural language processing capabilities using Azure AI Services.
• Utilizing GitHub Copilot to support AI-driven cloud application development.

This instructor-led live training in Gaia (online or onsite) targets intermediate-level data engineers who wish to become proficient in using Azure Synapse Analytics for a wide range of data processing, analytics, and visualization tasks.

By the end of this training, participants will be able to:

• Understand the core concepts, architecture, and components of Azure Synapse Analytics.
• Create, configure, and manage scalable data warehouses using Azure Synapse.
• Master the techniques for ingesting, transforming, and loading data (ETL) from various sources into Azure Synapse.
• Optimize query performance, secure data, and integrate Azure Synapse with Power BI and other tools to visualize data and share insights.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level data engineers who wish to learn how to use Azure Data Lake Storage Gen2 for effective data analytics solutions.

By the end of this training, participants will be able to:

• Understand the architecture and key features of Azure Data Lake Storage Gen2.
• Optimize data storage and access for cost and performance.
• Integrate Azure Data Lake Storage Gen2 with other Azure services for analytics and data processing.
• Develop solutions using the Azure Data Lake Storage Gen2 API.
• Troubleshoot common issues and optimize storage strategies.

In this instructor-led, live training in Gaia (online or onsite), participants will learn how to set up and manage a production-scale container environment using Kubernetes on AKS.

By the end of this training, participants will be able to:

• Configure and manage Kubernetes on AKS.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Azure.
• Migrate an existing Kubernetes environment from on-premise to AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

This instructor-led, live training in Gaia (online or onsite) targets developers and technical professionals at beginner, intermediate, and advanced levels who wish to use Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end of this training, participants will be able to understand AI agent architecture on Azure, create and configure a functional agent, link agents to business knowledge sources, and evaluate and prepare agents for deployment.

This instructor-led, live training in Gaia (available online or onsite) targets DevOps engineers, developers, and project managers who wish to utilize Azure DevOps to construct and deploy optimized enterprise applications more quickly than conventional development approaches permit.

By the end of this training, participants will be able to:

• Understand the fundamental DevOps vocabulary and principles.
• Install and configure the necessary Azure DevOps tools for software development.
• Utilize Azure DevOps tools and services to continuously adapt to the market.
• Build enterprise applications and evaluate current development processes upon Azure DevOps solutions.
• Manage teams more efficiently and accelerate software deployment time.
• Adopt DevOps development practices within the organization.

Azure Bot Service unites the capabilities of the Microsoft Bot Framework with Azure Functions, offering a robust platform for the rapid creation of intelligent bots.

During this instructor-led, live training, participants will discover how to efficiently develop intelligent bots using Microsoft Azure.

Upon completing the training, participants will be able to:

Grasp the fundamental concepts underpinning intelligent bots.

Construct intelligent bots using cloud-based applications.

Acquire practical expertise in the Microsoft Bot Framework, the Bot Builder SDK, and Azure Bot Service.

Implement established bot design patterns in real-world scenarios.

Create and deploy their first intelligent bot utilizing Microsoft Azure.

Audience

This course is tailored for developers, hobbyists, engineers, and IT professionals with an interest in bot development.

Course Format

The training integrates lectures and discussions with exercises, placing a strong emphasis on hands-on practice.

This instructor-led, live training (available online or onsite) is aimed at machine learning engineers who wish to utilise Azure Machine Learning and Azure DevOps to facilitate MLOps practices.

By the end of this training, participants will be able to:

• Build reproducible workflows and machine learning models.
• Manage the machine learning lifecycle.
• Track and report model version history, assets, and more.
• Deploy production ready machine learning models anywhere.