Introduction to Microsoft Azure and Azure Kubernetes Service Training Course

About This Course

In this course, students will learn how to design and develop services that access local and remote data from various sources. Students will also learn how to develop and deploy services to hybrid environments, including on-premises servers and Microsoft Azure.

Audience Profile

Primary: .NET developers who want to learn how to develop services and deploy them to hybrid environments.
Secondary: .NET developers with Web application development experience who are exploring developing new applications or porting existing applications to Microsoft Azure.

At Course Completion

After completing this course, students will be able to:

• Describe the basic concepts of service development and data access strategies using the .NET platform.
• Describe the Microsoft Azure cloud platform and its compute, data, and application hosting offerings.
• Design and develop a data-centric application using Visual Studio 2017 and Entity Framework Core.
• Design, implement, and consume HTTP services using ASP.NET Core.
• Extend HTTP services using ASP.NET Core.
• Host services on-premises and in Microsoft Azure.
• Deploy services to both on-premises and cloud environments and manage the interface and policy for their services.
• Choose a data storage solution, cache, distribute, and synchronize data.
• Monitor, log, and troubleshoot services.
• Describe claim-based identity concepts and standards, and implement authentication and authorization with Azure Active Directory.
• Create scalable service applications.

Acquire the essential knowledge required for designing Azure AI solutions by constructing a customer support chatbot utilizing artificial intelligence from the Microsoft Azure platform. This includes leveraging language understanding capabilities and pre-built AI functionality available through Azure Cognitive Services.

About This Course

This course introduces fundamental concepts related to artificial intelligence (AI) and the services available in Microsoft Azure for building AI solutions. It is not intended to train students to become professional data scientists or software developers; rather, it aims to raise awareness of common AI workloads and equip learners with the ability to identify appropriate Azure services to support them. The course is structured as a blended learning experience, combining instructor-led sessions with online resources on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises are based on Learn modules, and students are encouraged to use Learn content as reference material to reinforce classroom learning and explore topics in greater depth.

Audience Profile

The Azure AI Fundamentals course is designed for anyone interested in understanding the types of solutions artificial intelligence (AI) enables and the Microsoft Azure services that can be used to create them. No prior experience with Microsoft Azure is required; however, a basic familiarity with computer technology and the Internet is expected. Some concepts covered in the course require a foundational understanding of mathematics, such as the ability to interpret charts. The course includes practical activities involving data handling and code execution, so a basic knowledge of programming principles will be beneficial.

At Course Completion

Upon completing this course, you will be able to:

• Describe AI workloads and key considerations
• Explain the fundamental principles of machine learning on Azure
• Outline the features of computer vision workloads on Azure
• Outline the features of Natural Language Processing (NLP) workloads on Azure
• Outline the features of conversational AI workloads on Azure

This live, instructor-led training in Uzbekistan (online or onsite) is designed for intermediate to advanced-level professionals seeking 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 Uzbekistan (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 Azure's interactive workspace to collaboratively develop ML models.
• Choose from different Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.

About This Course

This three-day course is designed to help AWS (Amazon Web Services) developers prepare and build comprehensive end-to-end solutions on Microsoft Azure. Throughout the training, you will learn to create Azure App Service Web App solutions and Azure Functions, utilize blob storage or Cosmos DB, and implement secure cloud architectures that feature user authentication and authorization. You will also gain expertise in API management, developing event- and message-based architectures, as well as monitoring, troubleshooting, and optimizing your Azure deployments. The curriculum focuses on how developers leverage Azure services, highlighting key features and tasks that differ from AWS, and exploring what these distinctions mean for you when building applications hosted on Azure.

Audience Profile

This course is intended for experienced AWS developers who are looking to transition into or expand their skills in Azure development.

This course equips students with the essential knowledge and skills necessary to administer and automate the management of Windows servers using PowerShell. Learners will develop the ability to identify and construct the specific commands required to execute particular tasks. Additionally, students will learn how to write scripts to handle advanced operations, such as automating routine processes and generating reports. By mastering these prerequisite skills, participants will be better prepared to work with a wide variety of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. While the course does not concentrate on any single product, it uses Windows Server as the primary example, as it serves as the common platform for all the aforementioned technologies.

This course empowers IT professionals to effectively manage Azure subscriptions, safeguard identities, oversee infrastructure, configure virtual networks, link Azure with on-premises environments, handle network traffic, deploy storage solutions, build and scale virtual machines, establish web applications and containers, safeguard and share data, and monitor overall solution performance.

Designed for Azure Administrators, this training covers the implementation, management, and monitoring of identity, governance, storage, compute, and virtual networks within a cloud environment. Azure Administrators will learn to provision, size, monitor, and optimize resources as needed.

This course equips Azure administrators with the knowledge to plan, deliver, and manage virtual desktop experiences and remote applications for any device on Azure. Through a combination of demonstrations and hands-on lab exercises, students will learn to deploy and optimize virtual desktop environments and applications on Azure Virtual Desktop, ensuring they run efficiently in multi-session virtual settings.

About This Course

This course equips developers with the skills needed to build comprehensive end-to-end solutions in Microsoft Azure. Learners will gain expertise in implementing Azure compute resources, creating Azure Functions, and managing web applications. The curriculum covers developing solutions with Azure storage, enforcing authentication and authorization protocols, and securing applications using Key Vault and Managed Identities. Additionally, students will learn how to integrate Azure services and third-party solutions, incorporating event-driven and message-oriented architectures. The course also emphasizes monitoring, troubleshooting, and optimizing Azure-based solutions.

Audience Profile

• This course is designed for individuals interested in Azure development or those preparing to pass the Microsoft Azure Developer Associate certification exam.

This course empowers Solutions Architects to translate business needs into secure, scalable, and reliable solutions. Key lessons cover virtualization, automation, networking, storage, identity, security, data platforms, and application infrastructure, outlining how decisions in each area impact the overall solution.

Audience profile

Designed for IT Professionals skilled in designing and implementing solutions on Microsoft Azure. Participants should possess broad IT operations knowledge, including networking, virtualization, identity, security, business continuity, disaster recovery, data platforms, budgeting, and governance. Azure Solution Architects primarily use the Azure Portal, progressing to the Command Line Interface as their proficiency grows. Candidates must demonstrate expert-level Azure administration skills and experience with Azure development and DevOps processes.

DO180 offers a foundational guide to containers, the core principles of Kubernetes, and the concepts behind the Red Hat OpenShift platform, emphasizing practical, hands-on experience.

This instructor-led, live training session (available online or on-site) is designed for technical professionals at the beginner to intermediate level who aim to master container workflows, understand Kubernetes primitives, and learn how to deploy and manage applications on OpenShift.

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

• Construct and manage container images and registries, adhering to best practices for security and reproducibility.
• Deploy and administer Kubernetes objects, such as pods, deployments, and services, within OpenShift.
• Leverage OpenShift features like routes, buildconfigs, and the web console to accelerate application delivery.
• Implement persistent storage, configuration management, and secrets handling for stateful workloads.
• Apply fundamental security measures, RBAC, and monitoring practices to ensure the health of clusters and applications.

Course Format

• Interactive lectures and discussions.
• Daily hands-on labs conducted in a live OpenShift environment.
• Scenario-based exercises and troubleshooting workshops.

Customization Options

• For customized training arrangements for this course, please reach out to us.

This instructor-led, live training in Uzbekistan (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 guided, live training in Uzbekistan (online or on-site) is tailored for software developers and DevOps practitioners at beginner to intermediate levels who aim to master the setup and management of a local Kubernetes environment via Minikube.

Upon completing this training, participants will be equipped to:

• Install and configure Minikube on their local workstations.
• Grasp the fundamental concepts and architectural structure of Kubernetes.
• Deploy and oversee containers utilizing kubectl and the Minikube dashboard.
• Implement persistent storage and networking configurations for Kubernetes.
• Leverage Minikube for application development, testing, and debugging.

This instructor-led live training in Uzbekistan (online or onsite) is designed for intermediate-level developers and DevOps engineers who want to utilize Minikube as 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.