Designing and Implementing an Azure AI Solution (authorized training course AI 100T01) Training Course

About This Course

In this course, participants will acquire the skills to design and build services that retrieve data from both local and remote sources. Additionally, students will learn how to develop and deploy services within hybrid settings, encompassing on-premises servers and Microsoft Azure.

Audience Profile

Primary: .NET developers seeking to understand how to create services and deploy them to hybrid environments.
Secondary: .NET developers with experience in Web application development who are considering the development of new applications or migrating existing ones to Microsoft Azure.

At Course Completion

Upon finishing this course, students will be able to:

• Explain the fundamental concepts of service development and data access strategies utilising the .NET platform.
• Describe the Microsoft Azure cloud platform, including its compute, data, and application hosting capabilities.
• Design and develop a data-driven 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 interfaces and policies for these services.
• Select appropriate data storage solutions, and manage data caching, distribution, and synchronization.
• Monitor, log, and troubleshoot services.
• Explain claim-based identity concepts and standards, and implement authentication and authorisation with Azure Active Directory.
• Create scalable service applications.

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.

About This Course

This course introduces fundamental concepts relating to artificial intelligence (AI), alongside the services available in Microsoft Azure that can be leveraged to build AI solutions. The course is not designed to train 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 that 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 practical 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 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 solutions artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You do not need to have any prior experience 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 practical 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

This instructor-led, live training in Botswana (online or on-site) caters to intermediate to advanced professionals seeking to build and deploy AI-powered cloud applications using Microsoft Azure.

By the conclusion 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 Botswana (online or onsite) targets engineers who wish to utilise Azure ML's drag-and-drop platform to deploy machine learning workloads. This approach eliminates the need to purchase software and hardware and removes concerns regarding maintenance and deployment.

Upon completion 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 both machine learning and deep-learning models.
• Employ Azure's interactive workspace to collaboratively develop ML models.
• Select from various Azure-supported ML frameworks, including PyTorch, TensorFlow, and scikit-learn.

This course equips learners with the essential knowledge and competencies required to utilise PowerShell for the administration and automation of Windows server environments. Participants will develop the ability to identify and construct the necessary commands to execute specific tasks. Furthermore, students will acquire the skills to develop scripts that facilitate advanced operations, such as automating routine processes and producing reports. The content provides prerequisite capabilities that support a wide array of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. Aligned with this objective, the course does not concentrate on any single product; however, Windows Server serves as the exemplar for teaching these techniques, as it functions as the common platform for all the aforementioned 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 environments, manage network traffic, implement storage solutions, create and scale virtual machines, deploy web apps and containers, back up and share data, and monitor overall solutions.

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 adjust resources as required.

About This Course

This course equips developers with the skills to design and build comprehensive solutions within Microsoft Azure. Participants will learn to implement Azure compute options, develop Azure Functions, and manage web applications. The curriculum covers the utilisation of Azure storage services, the implementation of authentication and authorisation mechanisms, and the enhancement of security through Key Vault and Managed Identities. Students will also gain knowledge on integrating with Azure and third-party services, incorporating event-driven and messaging architectures into their solutions. Additionally, the course addresses the monitoring, troubleshooting, and optimisation of Azure-based solutions.

Audience Profile

• This course is suitable for individuals interested in Azure development or those preparing for the Microsoft Azure Developer Associate certification examination.

This programme equips participants with the knowledge and skills necessary to design and implement DevOps processes and practices. Learners will master planning for DevOps adoption, utilising source control, scaling Git within an enterprise environment, consolidating artifacts, designing dependency management strategies, managing secrets, implementing continuous integration, developing container build strategies, designing release strategies, establishing release management workflows, implementing deployment patterns, and optimising feedback mechanisms.

Audience profile

This course is ideal for professionals interested in designing and implementing DevOps processes, or those preparing for the Microsoft Azure DevOps Solutions certification examination.

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

This course equips IT security professionals with the knowledge and skills necessary to implement security controls, maintain an organization's security posture, and identify and remediate security vulnerabilities. The curriculum covers security for identity and access, platform protection, data and applications, and security operations.

Audience profile

This course is designed for Azure Security Engineers who are preparing to take the associated certification exam or who perform security-related tasks in their daily work. It is also beneficial for engineers seeking to specialize in providing security for Azure-based digital platforms and playing a pivotal role in protecting an organization's data.

Skills gained

• Implement enterprise governance strategies, including role-based access control, Azure policies, and resource locks.
• Deploy an Azure AD infrastructure, encompassing users, groups, and multi-factor authentication.
• Configure Azure AD Identity Protection, including risk policies, conditional access, and access reviews.
• Utilize Azure AD Privileged Identity Management for managing Azure AD roles and Azure resources.
• Set up Azure AD Connect, covering authentication methods and on-premises directory synchronization.
• Develop perimeter security strategies, including the use of Azure Firewall.
• Establish network security strategies, involving Network Security Groups and Application Security Groups.
• Enforce host security strategies, such as endpoint protection, remote access management, update management, and disk encryption.
• Secure container environments using Azure Container Instances, Azure Container Registry, and Azure Kubernetes.
• Configure Azure Key Vault to manage certificates, keys, and secrets.
• Implement application security strategies, including app registration, managed identities, and service endpoints.
• Secure storage solutions using shared access signatures, blob retention policies, and Azure Files authentication.
• Protect databases through authentication, data classification, dynamic data masking, and always encrypted features.
• Deploy Azure Monitor, including connected sources, log analytics, and alerts.
• Utilize Azure Security Center for policies, recommendations, and just-in-time virtual machine access.
• Configure Azure Sentinel, including workbooks, incidents, and playbooks.

About This Course

This course equips students with a solid understanding of Azure SQL Database and educates them on the requirements for migrating MySQL and PostgreSQL workloads to Azure SQL Database.

Audience Profile

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

At Course Completion

Upon finishing this course, students will have learned how to:

• 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 introduces students to the core principles of database concepts within a cloud setting, provides essential skills in cloud data services, and establishes a solid foundation for understanding cloud data services in Microsoft Azure. Participants will identify and describe key data concepts, including relational, non-relational, big data, and analytics, while exploring their implementation via Microsoft Azure. The curriculum also covers the roles, tasks, and responsibilities associated with the data sector. Students will examine relational data offerings, including the provisioning and deployment of relational databases, as well as querying relational data through cloud solutions in Azure. Furthermore, they will investigate non-relational data offerings, covering the provisioning and deployment of non-relational databases and data stores in Azure. The course explores available processing options for developing data analytics solutions in Azure, with a focus on Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Finally, students will gain an understanding of Power BI, its fundamental components, and how these elements interact.

Audience Profile

This course is designed for individuals who wish to learn the fundamental database concepts in a cloud environment, acquire basic skills in cloud data services, and build foundational knowledge of cloud data services within Microsoft Azure.

At Course Completion

Upon finishing 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

This intensive three-day programme is designed mainly for IT professionals who possess hands-on experience in managing on-premises Windows Server environments. Its goal is to equip these professionals with the skills needed to plan, deploy, and manage environments that incorporate Azure IaaS-hosted Windows Server-based workloads. The curriculum explores how to harness the hybrid capabilities of Azure, migrate both virtual and physical server workloads to Azure IaaS, and effectively manage and secure Azure VMs running Windows Server 2019.