Oversikt over relevante kurs innen IT-kurs i Rogaland

Modulen dekker bruk og effekt av Lean og agile arbeidsmåter, og hvordan dette kan utnyttes til fordel for organisasjonen. Kurset vil gi kandidatene en praktisk og strategisk metode for å planlegge og levere kontinuerlig forbedring med nødvendig smidighet.  E-læringskurset inneholder 18 timer med undervisning, og er delt inn i 12 moduler. Les mer om ITIL® 4 på AXELOS sine websider Du vil motta en e-post med tilgang til e-læringen, sertifiseringsvoucher og digital bok fra Peoplecert. Du avtaler tid for sertifiseringen som beskrevet i e-posten fra Peoplecert.   [-]

Kurset fokuserer på konvertering av etterspørsel til verdi via IT-relaterte tjenester. Modulen dekker sentrale emner som SLA-design, styring av flere leverandører, kommunikasjon, relasjonsstyring, CX- og UX-design, kartlegging av kunder og mer. E-læringskurset inneholder 18 timer med undervisning, og er delt inn i 8 moduler. Les mer om ITIL® 4 på  AXELOS sine websider. Du vil motta en e-post med tilgang til e-læringen, sertifiseringsvoucher og digital bok fra Peoplecert. Du avtaler tid for sertifiseringen som beskrevet i e-posten fra Peoplecert. [-]

ITIL® 4 Foundation-kurset er en introduksjon til ITIL® 4. Kurset lar kandidater se på IT-tjenestestyring gjennom en ende-til-ende driftsmodell, som inkluderer oppretting, levering og kontinuerlig forbedring av IT-relaterte produkter og tjenester. E-læringskurset inneholder 12 timer med undervisning, og er delt inn i 8 moduler. Les mer om ITIL® 4 på AXELOS sine websider. Inkluderer: Tilgang til ITIL® 4 Foundation e-læring (engelsk) i 12 måneder. ITIL® Foundation online voucher til sertifiseringstest + digital ITIL Foundation bok Du vil motta en e-post med tilgang til e-læringen, sertifiseringsvoucher og digital bok fra Peoplecert. Du avtaler tid for sertifiseringen som beskrevet i e-posten fra Peoplecert. Sertifiseringen består av: 40 spørsmål Multiple Choice 60 minutter + 15 minutter til rådighet dersom du ikke har engelsk som morsmål For å bestå må du ha minimum 26 riktige (65%) Ingen hjelpemidler tillatt ITIL®/PRINCE2®/MSP®/MoP® are registered trademarks of AXELOS Limited, used under permission of AXELOS Limited. All rights reserved. [-]

AZ-1008: Administer Active Directory Domain Services [-]

Dette grunnleggende kurset om Microsoft Power BI gir deg en solid forståelse av hvordan du kan bruke dette kraftige verktøyet for datainnsamling, analyse og visualisering. Med Power BI kan du effektivt samle inn, rense, transformere, analysere og presentere data fra forskjellige kilder. Dette kurset, ledet av data scientist Aina Øverås Skott, vil hjelpe deg med å mestre Power BI Desktop og Power BI Service, slik at du kan bruke dem effektivt i din profesjonelle karriere. Kurset dekker følgende emner: Kapittel 1: Introduksjon Kapittel 2: Behandle data Kapittel 3: Sette opp datamodell Kapittel 4: Case #1 Kapittel 5: Visualisere data Kapittel 6: Beregne og analysere data Kapittel 7: Publisere og dele rapporter Kapittel 8: Case #2 Kapittel 9: Veien videre   Varighet: 2 timer og 40 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Vår tjeneste fungerer på samme måte som strømmetjenester for musikk eller TV-serier, der våre kunder betaler en fast månedspris for tilgang til alle kursene vi har tilgjengelig. Vi har opplevd betydelig vekst de siste årene, med over 30 000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling engasjerende, spennende og tilgjengelig for alle, og vi har støtte fra Innovasjon Norge og Forskningsrådet. [-]

. 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.   TARGET AUDIENCE Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.   COURSE CONTENT Module 1: Creating Azure App Service Web Apps Students will learn how to build a web application on the Azure App Service platform. They will learn how the platform functions and how to create, configure, scale, secure, and deploy to the App Service platform. Azure App Service core concepts Creating an Azure App Service Web App Configuring and Monitoring App Service apps Scaling App Service apps Azure App Service staging environments Module 2: Implement Azure functions This module covers creating Functions apps, and how to integrate triggers and inputs/outputs in to the app. Azure Functions overview Developing Azure Functions Implement Durable Functions Module 3: Develop solutions that use blob storage Students will learn how Azure Blob storage works, how to manage data through the hot/cold/archive blob storage lifecycle, and how to use the Azure Blob storage client library to manage data and metadata. Azure Blob storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Module 4: Develop solutions that use Cosmos DB storage Students will learn how Cosmos DB is structured and how data consistency is managed. Students will also learn how to create Cosmos DB accounts and create databases, containers, and items by using a mix of the Azure Portal and the .NET SDK. Azure Cosmos DB overview Azure Cosmos DB data structure Working with Azure Cosmos DB resources and data Module 5: Implement IaaS solutions This module instructs students on how to use create VMs and container images to use in their solutions. It covers creating VMs, using ARM templates to automate resource deployment, create and manage Docker images, publishing an image to the Azure Container Registry, and running a container in Azure Container Instances. Provisioning VMs in Azure Create and deploy ARM templates Create container images for solutions Publish a container image to Azure Container Registry Create and run container images in Azure Container Instances Module 6: Implement user authentication and authorization Students will learn how to leverage the Microsoft Identity Platform v2.0 to manage authentication and access to resources. Students will also learn how to use the Microsoft Authentication Library and Microsoft Graph to authenticate a user and retrieve information stored in Azure, and how and when to use Shared Access Signatures. Microsoft Identity Platform v2.0 Authentication using the Microsoft Authentication Library Using Microsoft Graph Authorizing data operations in Azure Storage Module 7: Implement secure cloud solutions This module covers how to secure the information (keys, secrets, certificates) an application uses to access resources. It also covers securing application configuration information. Manage keys, secrets, and certificates by using the KeyVault API Implement Managed Identities for Azure resources Secure app configuration data by using Azure App Configuration Module 8: Implement API Management Students will learn how to publish APIs, create policies to manage information shared through the API, and to manage access to their APIs by using the Azure API Management service. API Management overview Defining policies for APIs Securing your APIs Module 9: Develop App Service Logic Apps This module teaches students how to use Azure Logic Apps to schedule, automate, and orchestrate tasks, business processes, workflows, and services across enterprises or organizations. Azure Logic Apps overview Creating custom connectors for Logic Apps Module 10: Develop event-based solutions Students will learn how to build applications with event-based architectures. Implement solutions that use Azure Event Grid Implement solutions that use Azure Event Hubs Implement solutions that use Azure Notification Hubs Module 11: Develop message-based solutions Students will learn how to build applications with message-based architectures. Implement solutions that use Azure Service Bus Implement solutions that use Azure Queue Storage queues Module 12: Monitor and optimize Azure solutions This module teaches students how to instrument their code for telemetry and how to analyze and troubleshoot their apps. Overview of monitoring in Azure Instrument an app for monitoring Analyzing and troubleshooting apps Implement code that handles transient faults Module 13: Integrate caching and content delivery within solutions Students will learn how to use different caching services to improve the performance of their apps. Develop for Azure Cache for Redis Develop for storage on CDNs [-]

Fleksible kurs for fremtiden Ny kunnskap skal gi umiddelbar effekt, og samtidig være holdbar og bærekraftig på lang sikt. NTI AS har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon.   Best practice i Part og Assemblie, tips og triks Ulike metoder på Skjellett-modellering. (Derived VS Multibody) Hvordan bruke Parametere Frame generator Flere Assemblie-features, Design View/ Level of Detail En kjapp innføring i iLogic Kurset vil også i en viss grad bli styrt ut ifra deltagernes spørsmål og ønsker   Her er et utvalg av temaene du vil lære på kurset: Intelligente konstruksjoner Sammenstillingsfunksjoner Konstruksjonsverktøyer Etter endt kurs vil du ha kunnskap og forståelse for oppbygning av definerte mekaniske konstruksjoner med Inventors avanserte designverktøy som f.eks. rammegenerator.Dessuten oppnår du en grundig kunnskap om håndtering og oppbygning av skjelettmodeller med bruk av ”Multi Bodies”.Du lærer å utnytte funksjoner som kan effektivisere håndteringen av samlinger.   Tilpassete kurs for bedrifter Vi vil at kundene våre skal være best på det de gjør - hele tiden.  Derfor tenker vi langsiktig om kompetanseutvikling og ser regelmessig kunnskapsløft som en naturlig del av en virksomhet. Vårt kurskonsept bygger på et moderne sett av ulike læringsmiljøer, som gjør det enkelt å finne riktig løsning uansett behov. Ta kontakt med oss på telefon 483 12 300, epost: salg@nticad.no eller les mer på www.nticad.no [-]

Confluence Essentials (server) [-]

 This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. TARGET AUDIENCE This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. COURSE CONTENT Module 1: Introduction to Azure Machine Learning In this module, you will learn how to provision an Azure Machine Learning workspace and use it to manage machine learning assets such as data, compute, model training code, logged metrics, and trained models. You will learn how to use the web-based Azure Machine Learning studio interface as well as the Azure Machine Learning SDK and developer tools like Visual Studio Code and Jupyter Notebooks to work with the assets in your workspace. Getting Started with Azure Machine Learning Azure Machine Learning Tools Lab : Creating an Azure Machine Learning WorkspaceLab : Working with Azure Machine Learning Tools After completing this module, you will be able to Provision an Azure Machine Learning workspace Use tools and code to work with Azure Machine Learning Module 2: No-Code Machine Learning with Designer This module introduces the Designer tool, a drag and drop interface for creating machine learning models without writing any code. You will learn how to create a training pipeline that encapsulates data preparation and model training, and then convert that training pipeline to an inference pipeline that can be used to predict values from new data, before finally deploying the inference pipeline as a service for client applications to consume. Training Models with Designer Publishing Models with Designer Lab : Creating a Training Pipeline with the Azure ML DesignerLab : Deploying a Service with the Azure ML Designer After completing this module, you will be able to Use designer to train a machine learning model Deploy a Designer pipeline as a service Module 3: Running Experiments and Training Models In this module, you will get started with experiments that encapsulate data processing and model training code, and use them to train machine learning models. Introduction to Experiments Training and Registering Models Lab : Running ExperimentsLab : Training and Registering Models After completing this module, you will be able to Run code-based experiments in an Azure Machine Learning workspace Train and register machine learning models Module 4: Working with Data Data is a fundamental element in any machine learning workload, so in this module, you will learn how to create and manage datastores and datasets in an Azure Machine Learning workspace, and how to use them in model training experiments. Working with Datastores Working with Datasets Lab : Working with DatastoresLab : Working with Datasets After completing this module, you will be able to Create and consume datastores Create and consume datasets Module 5: Compute Contexts One of the key benefits of the cloud is the ability to leverage compute resources on demand, and use them to scale machine learning processes to an extent that would be infeasible on your own hardware. In this module, you'll learn how to manage experiment environments that ensure consistent runtime consistency for experiments, and how to create and use compute targets for experiment runs. Working with Environments Working with Compute Targets Lab : Working with EnvironmentsLab : Working with Compute Targets After completing this module, you will be able to Create and use environments Create and use compute targets Module 6: Orchestrating Operations with Pipelines Now that you understand the basics of running workloads as experiments that leverage data assets and compute resources, it's time to learn how to orchestrate these workloads as pipelines of connected steps. Pipelines are key to implementing an effective Machine Learning Operationalization (ML Ops) solution in Azure, so you'll explore how to define and run them in this module. Introduction to Pipelines Publishing and Running Pipelines Lab : Creating a PipelineLab : Publishing a Pipeline After completing this module, you will be able to Create pipelines to automate machine learning workflows Publish and run pipeline services Module 7: Deploying and Consuming Models Models are designed to help decision making through predictions, so they're only useful when deployed and available for an application to consume. In this module learn how to deploy models for real-time inferencing, and for batch inferencing. Real-time Inferencing Batch Inferencing Lab : Creating a Real-time Inferencing ServiceLab : Creating a Batch Inferencing Service After completing this module, you will be able to Publish a model as a real-time inference service Publish a model as a batch inference service Module 8: Training Optimal Models By this stage of the course, you've learned the end-to-end process for training, deploying, and consuming machine learning models; but how do you ensure your model produces the best predictive outputs for your data? In this module, you'll explore how you can use hyperparameter tuning and automated machine learning to take advantage of cloud-scale compute and find the best model for your data. Hyperparameter Tuning Automated Machine Learning Lab : Tuning HyperparametersLab : Using Automated Machine Learning After completing this module, you will be able to Optimize hyperparameters for model training Use automated machine learning to find the optimal model for your data Module 9: Interpreting Models Many of the decisions made by organizations and automated systems today are based on predictions made by machine learning models. It's increasingly important to be able to understand the factors that influence the predictions made by a model, and to be able to determine any unintended biases in the model's behavior. This module describes how you can interpret models to explain how feature importance determines their predictions. Introduction to Model Interpretation using Model Explainers Lab : Reviewing Automated Machine Learning ExplanationsLab : Interpreting Models After completing this module, you will be able to Generate model explanations with automated machine learning Use explainers to interpret machine learning models Module 10: Monitoring Models After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes techniques for monitoring models and their data. Monitoring Models with Application Insights Monitoring Data Drift Lab : Monitoring a Model with Application InsightsLab : Monitoring Data Drift After completing this module, you will be able to Use Application Insights to monitor a published model Monitor data drift   [-]

MD-101: Managing Modern Desktops [-]

Modern Service Oriented Architecture [-]

COURSE OVERVIEW 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. TARGET AUDIENCE 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. COURSE OBJECTIVES  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   COURSE CONTENT Module 1: Introduction to AI In this module, you'll learn about common uses of artificial intelligence (AI), and the different types of workload associated with AI. You'll then explore considerations and principles for responsible AI development. Artificial Intelligence in Azure Responsible AI After completing this module you will be able to Describe Artificial Intelligence workloads and considerations Module 2: Machine Learning Machine learning is the foundation for modern AI solutions. In this module, you'll learn about some fundamental machine learning concepts, and how to use the Azure Machine Learning service to create and publish machine learning models. Introduction to Machine Learning Azure Machine Learning After completing this module you will be able to Describe fundamental principles of machine learning on Azure Module 3: Computer Vision Computer vision is a the area of AI that deals with understanding the world visually, through images, video files, and cameras. In this module you'll explore multiple computer vision techniques and services. Computer Vision Concepts Computer Vision in Azure After completing this module you will be able to Describe features of computer vision workloads on Azure Module 4: Natural Language Processing This module describes scenarios for AI solutions that can process written and spoken language. You'll learn about Azure services that can be used to build solutions that analyze text, recognize and synthesize speech, translate between languages, and interpret commands. After completing this module you will be able to Describe features of Natural Language Processing (NLP) workloads on Azure Module 5: Conversational AI Conversational AI enables users to engage in a dialog with an AI agent, or *bot*, through communication channels such as email, webchat interfaces, social media, and others. This module describes some basic principles for working with bots and gives you an opportunity to create a bot that can respond intelligently to user questions. Conversational AI Concepts Conversational AI in Azure After completing this module you will be able to Describe features of conversational AI workloads on Azure   TEST CERTIFICATION Recommended as preparation for the following exams: Exam AI-900: Microsoft Azure AI Fundamentals. HVORFOR VELGE SG PARTNER AS:  Flest kurs med Startgaranti Rimeligste kurs Beste service og personlig oppfølgning Tilgang til opptak etter endt kurs Partner med flere av verdens beste kursleverandører [-]

COURSE OVERVIEW . It also prepares delegates for the ITIL Foundation Certificate Examination. The course is based on the ITIL4 best practice service value system featured in the latest 2019 guidelines. TARGET AUDIENCE This course is aimed at all levels of IT professional and those involved in designing, building, delivering and managing modern digital products and services. COURSE OBJECTIVES After you complete this course you will be able to: Key IT service management concepts. How ITIL guiding principles can help and organization to adopt and adapt service management. The 4 dimensions of service management. The purpose and components of the service value system. The activities of the service value chain and how the interconnect. Know the purpose of key ITIL practices. Sit the ITIL4 foundation examination - Sample papers are set during the class by instructors to take during the class or as homework exercises. COURSE CONTENT IT Service Management definitions; Service, Utility, Warranty, Customer, User, Service management, Sponsor Key concepts of value creation Key concepts of service relationships; service offering; service provision; service consumption; service relationship management The nature, use and interaction of 7 ITIL guiding principles; Focus on value; Start where you are; Progress iteratively with feedback; Collaborate and promote visibility; Think and work holistically; Keep it simple and practical; Optimize and automate The 4 dimensions of service management; Organizations and people; Information and technology; Partners and suppliers; Value streams and processes    The ITIL service value system The service value chain, its inputs and outputs, and its role in supporting value streams Service value chain elements; Plan, Improve, Engage, Design & transition, Obtain / Build, Deliver & support Detail of how the following ITIL practices support the service value chain: -  Continual Improvement (including continual improvement model); Change control; Incident management; Problem Management; Service request management;  Service desk; Service level management The purpose of the following ITIL practices: - Information security management; Relationship management; Supplier management; Availability management; Capacity and performance management; Service configuration management;    IT asset management; Business analysis; Service continuity management; Deployment management; Monitoring and event management; Release management   TEST CERTIFICATION Recommended preparation for exam(s): ITIL4 Foundation Certificate in IT Service Management This is a pre-requisite for other ITIL4 qualifications. The examination is a 1 hour, closed book, multiple choice paper of 40 questions taken after completion of the course - exam vouchers are provided with this course. These will have a validity of 12 months. You will need to schedule your exams within this time frame. The pass mark is 65% (26 out of 40) Cost of the exam is included in the course fee [-]

MS-500: Microsoft 365 Security Administrator [-]

COURSE OVERVIEW These professionals manage and support an infrastructure that includes on-premises and Azure IaaS-hosted Windows Server-based workloads. The course teaches IT professionals 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. The course also covers how to perform tasks related to high availability, troubleshooting, and disaster recovery. The course highlights various administrative tools and technologies including Windows Admin Center, PowerShell, Azure Arc, Azure Automation Update Management, Microsoft Defender for Identity, Azure Security Center, Azure Migrate, and Azure Monitor. TARGET AUDIENCE This four-day course is intended for Windows Server Hybrid Administrators who have experience working with Windows Server and want to extend the capabilities of their on-premises environments by combining on-premises and hybrid technologies. Windows Server Hybrid Administrators who already implement and manage on-premises core technologies want to secure and protect their environments, migrate virtual and physical workloads to Azure Iaas, enable a highly available, fully redundant environment, and perform monitoring and troubleshooting. COURSE OBJECTIVES After you complete this course you will be able to: Harden the security configuration of the Windows Server operating system environment. Enhance hybrid security using Azure Security Center, Azure Sentinel, and Windows Update Management. Apply security features to protect critical resources. Implement high availability and disaster recovery solutions. Implement recovery services in hybrid scenarios. Plan and implement hybrid and cloud-only migration, backup, and recovery scenarios. Perform upgrades and migration related to AD DS, and storage. Manage and monitor hybrid scenarios using WAC, Azure Arc, Azure Automation and Azure Monitor. Implement service monitoring and performance monitoring, and apply troubleshooting. COURSE CONTENT Module 1: Windows Server security This module discusses how to protect an Active Directory environment by securing user accounts to least privilege and placing them in the Protected Users group. The module covers how to limit authentication scope and remediate potentially insecure accounts. The module also describes how to harden the security configuration of a Windows Server operating system environment. In addition, the module discusses the use of Windows Server Update Services to deploy operating system updates to computers on the network. Finally, the module covers how to secure Windows Server DNS to help protect the network name resolution infrastructure. Lessons for module 1 Secure Windows Sever user accounts Hardening Windows Server Windows Server Update Management Secure Windows Server DNS Lab : Configuring security in Windows Server Configuring Windows Defender Credential Guard Locating problematic accounts Implementing LAPS After completing module 1, students will be able to: Diagnose and remediate potential security vulnerabilities in Windows Server resources. Harden the security configuration of the Windows Server operating system environment. Deploy operating system updates to computers on a network by using Windows Server Update Services. Secure Windows Server DNS to help protect the network name resolution infrastructure. Implement DNS policies. Module 2: Implementing security solutions in hybrid scenarios This module describes how to secure on-premises Windows Server resources and Azure IaaS workloads. The module covers how to improve the network security for Windows Server infrastructure as a service (IaaS) virtual machines (VMs) and how to diagnose network security issues with those VMs. In addition, the module introduces Azure Security Center and explains how to onboard Windows Server computers to Security Center. The module also describes how to enable Azure Update Management, deploy updates, review an update assessment, and manage updates for Azure VMs. The modules explains how Adaptive application controls and BitLocker disk encryption are used to protect Windows Server IaaS VMs. Finally, the module explains how to monitor Windows Server Azure IaaS VMs for changes in files and the registry, as well as monitoring modifications made to application software. Lessons for module 2 Implement Windows Server IaaS VM network security. Audit the security of Windows Server IaaS Virtual Machines Manage Azure updates Create and implement application allowlists with adaptive application control Configure BitLocker disk encryption for Windows IaaS Virtual Machines Implement change tracking and file integrity monitoring for Windows Server IaaS VMs Lab : Using Azure Security Center in hybrid scenarios Provisioning Azure VMs running Windows Server Configuring Azure Security Center Onboarding on-premises Windows Server into Azure Security Center Verifying the hybrid capabilities of Azure Security Center Configuring Windows Server 2019 security in Azure VMs After completing module 2, students will be able to: Diagnose network security issues in Windows Server IaaS virtual machines. Onboard Windows Server computers to Azure Security Center. Deploy and manage updates for Azure VMs by enabling Azure Automation Update Management. Implement Adaptive application controls to protect Windows Server IaaS VMs. Configure Azure Disk Encryption for Windows IaaS virtual machines (VMs). Back up and recover encrypted data. Monitor Windows Server Azure IaaS VMs for changes in files and the registry. Module 3: Implementing high availability This module describes technologies and options to create a highly available Windows Server environment. The module introduces Clustered Shared Volumes for shared storage access across multiple cluster nodes. The module also highlights failover clustering, stretch clusters, and cluster sets for implementing high availability of Windows Server workloads. The module then discusses high availability provisions for Hyper-V and Windows Server VMs, such as network load balancing, live migration, and storage migration. The module also covers high availability options for shares hosted on Windows Server file servers. Finally, the module describes how to implement scaling for virtual machine scale sets and load-balanced VMs, and how to implement Azure Site Recovery. Lessons for module 3 Introduction to Cluster Shared Volumes. Implement Windows Server failover clustering. Implement high availability of Windows Server VMs. Implement Windows Server File Server high availability. Implement scale and high availability with Windows Server VMs. Lab : Implementing failover clustering Configuring iSCSI storage Configuring a failover cluster Deploying and configuring a highly available file server Validating the deployment of the highly available file server After completing module 3, students will be able to: Implement highly available storage volumes by using Clustered Share Volumes. Implement highly available Windows Server workloads using failover clustering. Describe Hyper-V VMs load balancing. Implement Hyper-V VMs live migration and Hyper-V VMs storage migration. Describe Windows Server File Server high availablity options. Implement scaling for virtual machine scale sets and load-balanced VMs. Implement Azure Site Recovery. Module 4: Disaster recovery in Windows Server This module introduces Hyper-V Replica as a business continuity and disaster recovery solution for a virtual environment. The module discusses Hyper-V Replica scenarios and use cases, and prerequisites to use it. The module also discusses how to implement Azure Site Recovery in on-premises scenarios to recover from disasters. Lessons for module 4 Implement Hyper-V Replica Protect your on-premises infrastructure from disasters with Azure Site Recovery Lab : Implementing Hyper-V Replica and Windows Server Backup Implementing Hyper-V Replica Implementing backup and restore with Windows Server Backup After completing module 4, students will be able to: Describe Hyper-V Replica, pre-requisites for its use, and its high-level architecture and components Describe Hyper-V Replica use cases and security considerations. Configure Hyper-V Replica settings, health monitoring, and failover options. Describe extended replication. Replicate, failover, and failback virtual machines and physical servers with Azure Site Recovery. Module 5: Implementing recovery services in hybrid scenarios This module covers tools and technologies for implementing disaster recovery in hybrid scenarios, whereas the previous module focus on BCDR solutions for on-premises scenarios. The module begins with Azure Backup as a service to protect files and folders before highlighting how to implementRecovery Vaults and Azure Backup Policies. The module describes how to recover Windows IaaS virtual machines, perform backup and restore of on-premises workloads, and manage Azure VM backups. The modules also covers how to provide disaster recovery for Azure infrastructure by managing and orchestrating replication, failover, and failback of Azure virtual machines with Azure Site Recovery. Lessons for module 5 Implement hybrid backup and recovery with Windows Server IaaS Protect your Azure infrastructure with Azure Site Recovery Protect your virtual machines by using Azure Backup Lab : Implementing Azure-based recovery services Implementing the lab environment Creating and configuring an Azure Site Recovery vault Implementing Hyper-V VM protection by using Azure Site Recovery vault Implementing Azure Backup After completing module 5, students will be able to: Recover Windows Server IaaS virtual machines by using Azure Backup. Use Azure Backup to help protect the data for on-premises servers and virtualized workloads. Implement Recovery Vaults and Azure Backup policies. Protect Azure VMs with Azure Site Recovery. Run a disaster recovery drill to validate protection. Failover and failback Azure virtual machines. Module 6: Upgrade and migrate in Windows Server This module discusses approaches to migrating Windows Server workloads running in earlier versions of Windows Server to more current versions. The module covers the necessary strategies needed to move domain controllers to Windows Server 2022 and describes how the Active Directory Migration Tool can consolidate domains within a forest or migrate domains to a new AD DS forest. The module also discusses the use of Storage Migration Service to migrate files and files shares from existing file servers to new servers running Windows Server 2022. Finally, the module covers how to install and use the Windows Server Migration Tools cmdlets to migrate commonly used server roles from earlier versions of Windows Server. Lessons for module 6 Active Directory Domain Services migration Migrate file server workloads using Storage Migration Service Migrate Windows Server roles Lab : Migrating Windows Server workloads to IaaS VMs Deploying AD DS domain controllers in Azure Migrating file server shares by using Storage Migration Service After completing module 6, students will be able to: Compare upgrading an AD DS forest and migrating to a new AD DS forest. Describe the Active Directory Migration Tool (ADMT). Identify the requirements and considerations for using Storage Migration Service. Describe how to migrate a server with storage migration. Use the Windows Server Migration Tools to migrate specific Windows Server roles. Module 7: Implementing migration in hybrid scenarios This module discusses approaches to migrating workloads running in Windows Server to an infrastructure as a service (IaaS) virtual machine. The module introduces using Azure Migrate to assess and migrate on-premises Windows Server instances to Microsoft Azure. The module also covers how migrate a workload running in Windows Server to an infrastructure as a service (IaaS) virtual machine (VM) and to Windows Server 2022 by using Windows Server migration tools or the Storage Migration Service. Finally, this module describes how to use the Azure Migrate App Containerization tool to containerize and migrate ASP.NET applications to Azure App Service. Lessons for module 7 Migrate on-premises Windows Server instances to Azure IaaS virtual machines Upgrade and migrate Windows Server IaaS virtual machines Containerize and migrate ASP.NET applications to Azure App Service Lab : Migrating on-premises VMs servers to IaaS VMs Implementing assessment and discovery of Hyper-V VMs using Azure Migrate Implementing migration of Hyper-V workloads using Azure Migrate After completing module 7, students will be able to: Plan a migration strategy and choose the appropriate migration tools. Perform server assessment and discovery using Azure Migrate. Migrate Windows Server workloads to Azure VM workloads using Azure Migrate. Explain how to migrate workloads using Windows Server Migration tools. Migrate file servers by using the Storage Migration Service. Discover and containerize ASP.NET applcations running on Windows. Migrate a containerized application to Azure App Service. Module 8: Server and performance monitoring in Windows Server This module introduces a range of tools to monitor the operating system and applications on a Windows Server computer as well as describing how to configure a system to optimize efficiency and to troublshoot problems. The module covers how Event Viewer provides a convenient and accessible location for observing events that occur, and how to interpret the data in the event log. The module also covers how to audit and diagnose a Windows Server environment for regulatory compliance, user activity, and troubleshooting. Finally, the module explains how to troubleshoot AD DS service failures or degraded performance, including recovery of deleted objects and the AD DS database, and how to troubleshoot hybrid authentication issues. Lessons for module 8 Monitor Windows Server performance Manage and monitor Windows Server event logs Implement Windows Server auditing and diagnostics Troubleshoot Active Directory Lab : Monitoring and troubleshooting Windows Server Establishing a performance baseline Identifying the source of a performance problem Viewing and configuring centralized event logs After completing module 8, students will be able to: Explain the fundamentals of server performance tuning. Use built-in tools in Windows Server to monitor server performance. Use Server Manager and Windows Admin Center to review event logs. Implement custom views. Configure an event subscription. Audit Windows Server events. Configure Windows Server to record diagnostic information. Recover the AD DS database and objects in AD DS. Troubleshoot AD DS replication. Troubleshoot hybrid authentication issues. Module 9: Implementing operational monitoring in hybrid scenarios This module covers using monitoring and troubleshooing tools, processes, and best practices to streamline app performance and availabilty of Windows Server IaaS VMs and hybrid instances. The module describes how to implement Azure Monitor for IaaS VMs in Azure, implement Azure Monitor in on-premises environments, and use dependency maps. The module then explains how to enable diagnostics to get data about a VM, and how to view VM metrics in Azure Metrics Explorer, and how to create a metric alert to monitor VM performance. The module then covers how to monitor VM performance by using Azure Monitor VM Insights. The module then describes various aspects of troubleshooting on premises and hybrid network connectivity, including how to diagnose common issues with DHCP, name resolution, IP configuration, and routing. Finally, the module examines how to troubleshoot configuration issues that impact connectivity to Azure-hosted Windows Server virtual machines (VMs), as well as approaches to resolve issues with VM startup, extensions, performance, storage, and encryption. Lessons for module 9 Monitor Windows Server IaaS Virtual Machines and hybrid instances Monitor the health of your Azure virtual machines by using Azure Metrics Explorer and metric alerts Monitor performance of virtual machines by using Azure Monitor VM Insights Troubleshoot on-premises and hybrid networking Troubleshoot Windows Server Virtual Machines in Azure Lab : Monitoring and troubleshooting of IaaS VMs running Windows Server Enabling Azure Monitor for virtual machines Setting up a VM with boot diagnostics Setting up a Log Analytics workspace and Azure Monitor VM Insights After completing module 9, students will be able to: Implement Azure Monitor for IaaS VMs in Azure and in on-premises environments. Implement Azure Monitor for IaaS VMs in Azure and in on-premises environments. View VM metrics in Azure Metrics Explorer. Use monitoring data to diagnose problems. Evaluate Azure Monitor Logs and configure Azure Monitor VM Insights. Configure a Log Analytics workspace. Troubleshoot on-premises connectivity and hybrid network connectivity. Troubleshoot AD DS service failures or degraded performance. Recover deleted security objects and the AD DS database. Troubleshoot hybrid authentication issues. [-]