Architecting Microsoft Azure Solutions Training Course

This instructor-led, live training in Australia (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to build and deploy AI-powered cloud applications using Microsoft Azure.

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

• Develop event-driven and serverless applications using Azure Functions.
• Manage Azure storage solutions and virtual machines.
• Deploy and scale web applications using Azure App Service and Docker containers.
• Integrate AI, machine learning, and natural language processing using Azure AI Services.
• Leverage GitHub Copilot to assist in AI-driven cloud application development.

This instructor-led, live training in Australia (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level developers and technical professionals 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 working agent, connect agents to business knowledge sources, evaluate and prepare agents for deployment.

This instructor-led, live training in Australia (online or onsite) is designed for DevOps engineers, developers, and project managers who wish to utilise Azure DevOps to build and deploy optimised enterprise applications more quickly than traditional development methods.

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

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

This instructor-led, live training in Australia (online or onsite) is designed for security administrators aiming to secure Azure workloads.

Upon completing this training, participants will be able to:

• Manage host security, network security, and additional areas.
• Configure storage and database security in Azure.
• Implement security monitoring using Azure resources.
• Prevent malicious cyber attacks targeting data and infrastructures.

This instructor-led live training, conducted Australia (either online or on-site), is targeted at security administrators who wish to learn how to configure Azure cloud security to protect workloads running in Azure.

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

• Configure host and network security.
• Configure Azure advanced security options.
• Use Azure to secure cloud computing workloads.
• Use endpoint protection services security against malware and viruses.
• Secure container workloads that are running in Azure.

Azure Bot Service unites the power of the Microsoft Bot Framework with Azure Functions, offering a robust platform for rapidly creating intelligent bots.

In this instructor-led, live training, participants will discover efficient methods for developing intelligent bots using Microsoft Azure.

Upon completing the training, participants will be capable of:

Grasping the fundamental concepts behind intelligent bots.

Constructing intelligent bots using cloud-based applications.

Acquiring practical knowledge of the Microsoft Bot Framework, the Bot Builder SDK, and Azure Bot Service.

Applying established bot design patterns to real-world scenarios.

Creating and deploying their first intelligent bot using Microsoft Azure.

Target Audience

This course is tailored for developers, hobbyists, engineers, and IT professionals keen on bot development.

Course Format

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

This instructor-led, live training in Australia (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.
• Optimise 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 optimise storage strategies.

This instructor-led, live training in Australia (online or onsite) is designed for intermediate-level Java developers, software engineers, and cloud enthusiasts who want to leverage the capabilities of Azure OpenAI to build intelligent applications.

Upon completing this training, participants will be able to:

• Grasp the fundamental principles of Generative AI and its practical applications.
• Configure and manage an Azure OpenAI service.
• Integrate OpenAI models into Java applications.
• Deploy AI-driven features within web applications.

In this instructor-led, live training in Australia (onsite or remote) participants will learn the fundamental concepts, components, and services of Microsoft Azure as they step through the creation of a sample cloud application.

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

• Understand the basics of Microsoft Azure
• Understand the different Azure tools and services
• Learn how to use Azure for building cloud applications

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

Upon completion of this training, participants will be able to:

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

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

Upon completion of this training, participants will be able to:

• Develop reproducible workflows and machine learning models.
• Oversee the machine learning lifecycle.
• Monitor and report on model version history, assets, and other details.
• Deploy production-ready machine learning models in any environment.

This instructor-led, live training in Australia (online or on-site) is aimed at intermediate-level data engineers who wish to become proficient in utilizing Azure Synapse Analytics for a wide range of data processing, analytics, and visualisation.

By the conclusion 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 visualise data and share insights.

This instructor-led, live training in Australia (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.