Kubernetes on Azure (AKS)のトレーニングコース

This instructor-led, live training in 日本 (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 日本 (online or onsite) is aimed at engineers who wish to use Azure ML's drag-and-drop platform to deploy Machine Learning workloads without having to purchase software and hardware and without having to worry about maintenance and deployment.

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

• Write highly-accurate machine learning models using Python, R, or zero-code tools.
• Leverage Azure's available data sets and algorithms to train and track machine learning and deep-learning models.
• Use Azures interactive workspace to collaboratively develop ML models.
• Choose from different Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.

Microsoft Azure Infrastructure and Deployment

This training permits delegates to improve their Microsoft Azure solution design skills.

After this training the delegate will understand the features and capabilities of Azure services, to be able to identify trade-offs, and make decisions for designing public and hybrid cloud solutions.

During training the appropriate infrastructure and platform solutions to meet the required functional, operational, and deployment requirements through the solution life-cycle will be defined.

This instructor-led, live training in 日本 (online or onsite) is aimed at DevOps engineers, developers, and project managers who wish to utilize Azure DevOps to build and deploy optimized enterprise applications faster than traditional development approaches.

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.

This instructor-led, live training in 日本 (online or onsite) is aimed at data scientists who wish to use Azure Machine Learning to build end-to-end machine learning models for predictive analysis.

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

• Build machine learning models with zero programming experience.
• Create predictive algorithms with Azure Machine Learning.
• Deploy production ready machine learning algorithms.

This instructor-led, live training in 日本 (online or onsite) is aimed at security administrators who wish to secure Azure workloads.

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

• Administrate host security, network security, and more.
• Set up storage and database security in Azure.
• Implement security monitoring using Azure resources.
• Prevent malicious cyber attacks on data and infrastructures.

This instructor-led, live training in 日本 (online or onsite) is aimed at security administrators who wish to learn how to configure Azure cloud security to secure 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.

This instructor-led, live training in 日本 (online or onsite) is aimed at developers who wish 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.

The Azure Bot Service combines the power of the Microsoft Bot Framework and Azure functions to enable rapid development of intelligent bots.

In this instructor-led, live training, participants will learn how to easily create an intelligent bot using Microsoft Azure

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

• Learn the fundamentals of intelligent bots
• Learn how to create intelligent bots using cloud applications
• Understand how to use the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Understand how to design bots using bot patterns
• Develop their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This instructor-led, live training in 日本 (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.

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level Java developers, software engineers, and cloud enthusiasts who wish to harness the power of Azure OpenAI to create intelligent applications.

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

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

This instructor-led, live training in 日本 (online or onsite) is aimed at engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level to intermediate-level software developers and DevOps professionals who wish to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machine.
• Understand the basic concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Utilize Minikube for developing, testing, and debugging applications.

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to use Minikube as a part of their development workflow.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.