Azure DevOps Fundamentals Training Course

This instructor-led, live training in New Zealand (online or onsite) is designed for intermediate to advanced-level professionals who aim 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 New Zealand (online or onsite) is designed for engineers who wish to leverage Azure ML's drag-and-drop platform to deploy Machine Learning workloads without the need to purchase software and hardware, or worry about maintenance and deployment.

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

• Develop highly accurate machine learning models using Python, R, or zero-code tools.
• Utilise Azure's available datasets and algorithms to train and track machine learning and deep-learning models.
• Use Azure's interactive workspace to collaboratively develop ML models.
• Select from a range of Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.

Microsoft Azure Infrastructure and Deployment

This instructor-led, live training in New Zealand (online or on-site) is targeted at beginner, intermediate, and advanced developers and technical professionals who wish to leverage Microsoft Azure to build, test, and deploy AI agents for business applications.

By the conclusion of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a working agent, integrate agents with business knowledge sources, evaluate and prepare agents for deployment.

This training enables delegates to enhance their Microsoft Azure solution design skills.

Upon completion, participants will understand the features and capabilities of Azure services, allowing them to identify trade-offs and make informed decisions when designing public and hybrid cloud solutions.

Throughout the training, delegates will define appropriate infrastructure and platform solutions that meet functional, operational, and deployment requirements across the solution lifecycle.

This instructor-led, live training in New Zealand (available online or on-site) is designed for data scientists who wish to use Azure Machine Learning to develop end-to-end machine learning models for predictive analytics.

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

• Build machine learning models with no prior programming experience.
• Create predictive algorithms using Azure Machine Learning.
• Deploy production-ready machine learning algorithms.

This instructor-led, live training in New Zealand (available online or on-site) is tailored for security administrators seeking to secure Azure workloads.

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

• Administer host security, network security, and more.
• Configure storage and database security within Azure.
• Implement security monitoring using Azure resources.
• Prevent malicious cyber attacks against data and infrastructure.

This instructor-led, live training in New Zealand (online or on-site) is designed for 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.
• Implement endpoint protection services to defend against malware and viruses.
• Secure container workloads running in Azure.

This instructor-led, live training in New Zealand (online or on-site) is designed for developers who want to learn how to build microservices on Microsoft Azure Service Fabric (ASF).

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

• Use ASF as a platform for building and managing microservices.
• Understand key microservices programming concepts and models.
• Create a cluster in Azure.
• Deploy microservices on-premises or in the cloud.
• Debug and troubleshoot a live microservice application.

Azure Bot Service combines the capabilities of the Microsoft Bot Framework and Azure Functions, delivering a robust platform for rapidly building intelligent bots.

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

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

Grasp the core concepts underpinning intelligent bots.

Build intelligent bots using cloud-based applications.

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

Apply proven bot design patterns to real-world scenarios.

Create and deploy their first intelligent bot using Microsoft Azure.

Audience

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

Format of the course

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

This instructor-led, live training in New Zealand (available online or on-site) is tailored for intermediate-level data engineers who want to learn how to leverage 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 efficiency 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 refine storage strategies.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level Java developers, software engineers, and cloud enthusiasts who want to leverage Azure OpenAI to build intelligent applications.

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

• Understand the core principles of Generative AI and its practical applications.
• Set up and manage an Azure OpenAI service.
• Integrate OpenAI's models into Java applications.
• Deploy AI-driven features within web applications.

In this instructor-led, live training in New Zealand (onsite or remote), participants will explore the fundamental concepts, components, and services of Microsoft Azure while stepping 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
• Gain familiarity with the range of Azure tools and services
• Learn how to leverage Azure for building cloud applications

The Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, enabling them to communicate with one another and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive suite of cloud services, including an IoT Suite composed of preconfigured solutions that help developers accelerate the development of IoT projects.

In this instructor-led, live training, participants will learn how to develop IoT applications using Azure.

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

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Appreciate the benefits of using Azure in programming IoT systems
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

• To request customised training for this course, please contact us to make arrangements.

This instructor-led, live training in New Zealand (online or on-site) is designed for engineers who wish to deploy Machine Learning workloads to the Azure cloud.

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

• Install and configure Kubernetes, Kubeflow, and other required software on Azure.
• Use Azure Kubernetes Service (AKS) to simplify the process of initialising a Kubernetes cluster on Azure.
• Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
• Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
• Leverage other AWS managed services to extend an ML application.