AZ-104T00-A: Microsoft Azure Administrator Training Course

This instructor-led, live training in Slovakia (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.

About This Course

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

Audience Profile

The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, 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

About This Course

In this course, students will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will identify and describe core data concepts such as relational, non-relational, big data, and analytics, and explore how this technology is implemented with Microsoft Azure. They will explore the roles, tasks, and responsibilities in the world of data. The students will explore relational data offerings, provisioning and deploying relational databases, and querying relational data through cloud data solutions with Microsoft Azure. They will explore non-relational data offerings, provisioning and deploying non-relational databases, and non-relational data stores with Microsoft Azure. Students will explore the processing options available for building data analytics solutions in Azure. They will explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Students will learn what Power BI is, including its building blocks and how they work together.

Audience Profile

The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.

At Course Completion

After completing this course, students will be able to:

• Describe core data concepts in Azure
• Explain concepts of relational data in Azure
• Explain concepts of non-relational data in Azure
• Identify components of a modern data warehouse in Azure

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.

Gain the necessary knowledge for designing Azure AI solution by building a customer support chat Bot using artificial intelligence from the Microsoft Azure platform including language understanding and pre-built AI functionality in the Azure Cognitive Services.

About This Course

This two-day course is designed for AWS Sysops administrators interested in learning how Azure is different from AWS, and how Azure is administered. The workshops main topics are Azure Administration, Azure Networking, Azure Compute, Azure Storage, and Azure Governance. This workshop combines lecture with hands-on practical exercises and discussion/review. During the workshop students will build an end-to-end architecture that demonstrates the main features discussed in the course.

Audience Profile

The audience for this course is an AWS Sysops Administrator Associate or equivalent. This person has one to two years of experience in AWS deployment, management, and operations. Students taking this course are interested in learning how Azure is different from AWS, and how Azure is administered. Students may also be interested in taking the AZ-103 Microsoft Azure Administrator certification exam, or the AZ-900 Azure Fundamentals exam.

About This Course

A three-day course designed to teach AWS (Amazon Web Services) developers how to prepare end-to-end solutions in Microsoft Azure. In this course you will construct Azure App Service Web App solutions and Azure Functions, use blob or Cosmos DB storage in solutions, implement secure cloud solutions that include user authentication and authorization, implement API management, and develop event- and message-based solutions, and monitor, troubleshoot, and optimize your Azure solutions. You will learn how developers use Azure services, with additional focus on features and tasks that differ from AWS, and what that means for you as you develop applications that will be hosted by using Azure services.

Audience Profile

Students in this course are experienced AWS developers interested in Azure development.

About This Course

This course will enable the students to understand Azure SQL Database, and educate the students on what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database.

Audience Profile

The primary audience for this course is database developers who plan to migrate their MySQL or Postgres DB workloads to Azure SQL DB. The secondary audience for this course is MySQL/Postgres administrators to raise awareness of the features and benefits of Azure SQL DB.

At Course Completion

At the end of this course, the students will have learned:

• Migrate on-premises MySQL to Azure SQL DB for MySQL
• Migrate on-premises PostgreSQL to Azure SQL DB for PostgreSQL

About This Course

This course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions.

Audience Profile

• Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.

This three-day course is intended primarily for IT Professionals who have experience with managing an on-premises Windows Server environment. Its purpose is to prepare professionals for planning, implementing, and managing environments that include Azure IaaS-hosted Windows Server-based workloads. The course covers how to leverage the hybrid capabilities of Azure, how to migrate virtual and physical server workloads to Azure IaaS, and how to manage and secure Azure VMs running Windows Server 2019.

This course provides IT Security Professionals with the knowledge and skills needed to implement security controls, maintain an organization’s security posture, and identify and remediate security vulnerabilities. This course includes security for identity and access, platform protection, data and applications, and security operations.

Audience profile

This course is for Azure Security Engineers who are planning to take the associated certification exam, or who are performing security tasks in their day-to-day job. This course would also be helpful to an engineer that wants to specialize in providing security for Azure-based digital platforms and play an integral role in protecting an organization's data.

Skills gained

• Implement enterprise governance strategies including role-based access control, Azure policies, and resource locks.
• Implement an Azure AD infrastructure including users, groups, and multi-factor authentication.
• Implement Azure AD Identity Protection including risk policies, conditional access, and access reviews.
• Implement Azure AD Privileged Identity Management including Azure AD roles and Azure resources.
• Implement Azure AD Connect including authentication methods and on-premises directory synchronization.
• Implement perimeter security strategies including Azure Firewall.
• Implement network security strategies including Network Security Groups and Application Security Groups.
• Implement host security strategies including endpoint protection, remote access management, update management, and disk encryption.
• Implement container security strategies including Azure Container Instances, Azure Container Registry, and Azure Kubernetes.
• Implement Azure Key Vault including certificates, keys, and secretes.
• Implement application security strategies including app registration, managed identities, and service endpoints.
• Implement storage security strategies including shared access signatures, blob retention policies, and Azure Files authentication.
• Implement database security strategies including authentication, data classification, dynamic data masking, and always encrypted.
• Implement Azure Monitor including connected sources, log analytics, and alerts.
• Implement Azure Security Center including policies, recommendations, and just in time virtual machine access.
• Implement Azure Sentinel including workbooks, incidents, and playbooks.

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.

Audience Profile

Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms.

Audience profile

Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam.

Job role: DevOps Engineer

Preparation for exam: AZ-400

Skills gained

• Plan for the transformation with shared goals and timelines
• Select a project and identify project metrics and Key Performance Indicators (KPI's)
• Create a team and agile organizational structure
• Design a tool integration strategy
• Design a license management strategy (e.g. Azure DevOps and GitHub users)
• Design a strategy for end-to-end traceability from work items to working software
• Design an authentication and access strategy
• Design a strategy for integrating on-premises and cloud resources
• Describe the benefits of using Source Control
• Describe Azure Repos and GitHub
• Migrate from TFVC to Git
• Manage code quality including technical debt SonarCloud, and other tooling solutions
• Build organizational knowledge on code quality
• Explain how to structure Git repos
• Describe Git branching workflows
• Leverage pull requests for collaboration and code reviews
• Leverage Git hooks for automation
• Use Git to foster inner source across the organization
• Explain the role of Azure Pipelines and its components
• Configure Agents for use in Azure Pipelines
• Explain why continuous integration matters
• Implement continuous integration using Azure Pipelines
• Define Site Reliability Engineering
• Design processes to measure end-user satisfaction and analyze user feedback
• Design processes to automate application analytics
• Manage alerts and reduce meaningless and non-actionable alerts
• Carry out blameless retrospectives and create a just culture
• Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure
• Implement compliance and security in your application infrastructure
• Describe the potential challenges with integrating open-source software
• Inspect open-source software packages for security and license compliance
• Manage organizational security and compliance policies
• Integrate license and vulnerability scans into build and deployment pipelines
• Configure build pipelines to access package security and license ratings

In this whiteboard design session, you will learn how to design a solution with a combination of Azure Resource Manager templates and Azure DevOps to enable continuous delivery with several Azure PaaS services.

At the end of this workshop, you will be better able to build templates to automate cloud infrastructure and reduce error-prone manual processes. In addition, you'll create an Azure Resource Manager (ARM) template to provision Azure resources, configure continuous delivery with Azure DevOps, configure Application Insights into an application, and create an Azure DevOps project and Git repository.

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.