Introduction to Microsoft Azure and Azure Kubernetes Service Training Course

About This Course

In this course, participants will acquire the skills to design and develop services that interact with local and remote data from diverse sources. Additionally, learners will master the process of deploying services to hybrid environments, encompassing both on-premises servers and Microsoft Azure.

Audience Profile

Primary: .NET developers seeking to learn how to create services and deploy them within hybrid environments.
Secondary: .NET developers with prior web application development experience who are interested in building new applications or migrating existing ones to Microsoft Azure.

At Course Completion

Upon finishing this course, students will be equipped to:

• Explain the fundamental concepts of service development and data access strategies using the .NET platform.
• Describe the Microsoft Azure cloud platform, along with its compute, data, and application hosting offerings.
• Design and develop data-centric applications utilizing Visual Studio 2017 and Entity Framework Core.
• Design, implement, and consume HTTP services using ASP.NET Core.
• Extend HTTP services via ASP.NET Core.
• Host services both on-premises and within Microsoft Azure.
• Deploy services to on-premises and cloud environments, and manage their service interfaces and policies.
• Select appropriate data storage solutions, and manage data caching, distribution, and synchronization.
• Monitor, log, and troubleshoot services.
• Describe claim-based identity concepts and standards, and implement authentication and authorization using Azure Active Directory.
• Create scalable service applications.

Acquire the essential skills required to design Azure AI solutions by constructing a customer support chatbot leveraging artificial intelligence on the Microsoft Azure platform. This includes implementing language understanding capabilities and utilising pre-built AI functionalities available through Azure Cognitive Services.

About This Course

This course provides an introduction to the core concepts of artificial intelligence (AI) and the Microsoft Azure services available for building AI solutions. The program is not intended to train students to become professional data scientists or software developers; instead, it aims to build awareness of common AI workloads and the ability to identify appropriate Azure services to support them. Designed as a blended learning experience, the course combines instructor-led training with online materials 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 a reference 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 that artificial intelligence (AI) enables, and the Microsoft Azure services available to create them. No prior experience with Microsoft Azure is required, though a basic familiarity with computer technology and the Internet is assumed. Some concepts covered require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities involving data work and code execution, so a knowledge of fundamental programming principles will be helpful.

At Course Completion

After completing this course, you will be able to:

• Describe Artificial Intelligence workloads and considerations
• Describe fundamental principles of machine learning on Azure
• Describe features of computer vision workloads on Azure
• Describe features of Natural Language Processing (NLP) workloads on Azure
• Describe features of conversational AI workloads on Azure

This live, instructor-led training in Kenya (online or onsite) is designed for intermediate to advanced professionals aiming 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 (available online or onsite) is designed for 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.

About This Course

This intensive three-day programme is tailored for AWS (Amazon Web Services) developers aiming to design and build comprehensive solutions on Microsoft Azure. Throughout the course, you will master the construction of Azure App Service Web Apps and Azure Functions, integrate blob or Cosmos DB storage, and implement secure cloud architectures involving user authentication and authorisation. You will also gain proficiency in API management, develop event- and message-driven solutions, and learn critical techniques for monitoring, troubleshooting, and optimising your Azure deployments. The training highlights how developers leverage Azure services, with a specific emphasis on features and tasks that diverge from AWS, enabling you to effectively adapt your application development practices for the Azure environment.

Audience Profile

This course is designed for experienced AWS developers who are keen to transition into Azure development.

This course equips learners with the essential knowledge and skills required to administer and automate Windows server environments using PowerShell. Participants will develop the ability to identify and construct the necessary commands to execute specific tasks. Furthermore, students will learn to build scripts for advanced operations, such as automating routine activities and generating reports. The course provides prerequisite skills applicable to a wide array of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. Aligning with this objective, the course does not concentrate on a single product; however, Windows Server serves as the primary example platform for the techniques taught, as it is the common foundation for these products.

This course equips IT Professionals with the skills to manage Azure subscriptions, secure identities, administer infrastructure, configure virtual networking, connect Azure with on-premises sites, manage network traffic, implement storage solutions, create and scale virtual machines, deploy web apps and containers, back up and share data, and monitor your solutions.

This course is designed for Azure Administrators. The Azure Administrator manages, implements, and monitors identity, governance, storage, compute, and virtual networks within a cloud environment. The Azure Administrator provisions, sizes, monitors, and adjusts resources as necessary.

This course equips Azure administrators with the skills to plan, deliver, and manage virtual desktop experiences and remote applications for any device on Azure. Through a combination of demonstrations and hands-on labs, students will deploy virtual desktop environments and applications on Azure Virtual Desktop, learning to optimize them for multi-session virtual environments.

About This Course

This course equips developers with the skills to build end-to-end solutions on Microsoft Azure. Participants will learn how to implement Azure compute solutions, create Azure Functions, and implement and manage web applications. The curriculum covers developing solutions that leverage Azure storage, implementing authentication and authorization, and securing solutions through KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services as well as third-party services, incorporating event- and message-based models into their solutions. Additionally, the course addresses the monitoring, troubleshooting, and optimization of Azure solutions.

Audience Profile

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

This course equips Solutions Architects with the skills to translate business requirements into secure, scalable, and reliable cloud solutions. Key topics include virtualization, automation, networking, storage, identity management, security, data platforms, and application infrastructure. The curriculum explains how decisions in each of these areas impact the overall solution architecture.

Audience profile

This course is designed for IT Professionals who specialize in designing and implementing solutions on Microsoft Azure. Participants should possess broad knowledge of IT operations, covering networking, virtualization, identity, security, business continuity, disaster recovery, data platforms, budgeting, and governance. Azure Solution Architects utilize the Azure Portal and, as their proficiency grows, the Command Line Interface. Candidates must demonstrate expert-level skills in Azure administration, along with experience in Azure development and DevOps processes.

DO180 provides a foundational introduction to containers, Kubernetes core concepts, and Red Hat OpenShift platform principles, emphasizing practical, hands-on learning.

This live, instructor-led training, available either online or onsite, 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 able to:

• Create and manage container images and registries, adhering to best practices for security and reproducibility.
• Deploy and administer Kubernetes resources, including pods, deployments, and services, within OpenShift.
• Leverage OpenShift capabilities such as routes, BuildConfigs, and the web console to streamline application delivery.
• Configure persistent storage, manage configurations, and handle secrets for stateful workloads.
• Apply fundamental security measures, Role-Based Access Control (RBAC), and monitoring practices to ensure cluster and application health.

Course Format

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

Course Customization Options

• For tailored training requests, please contact us to discuss arrangements.

This instructor-led, live training in Kenya (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 Kenya (online or in-person) is designed for beginner 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 Kenya (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.