Oversikt over relevante kurs innen Kurs i programvare og applikasjoner i Nordland

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Generelt gode IT-kunnskaper. Bør ha kjennskap til bruk av Windows server og fordel med MS SQL server. Kjennskap til AD, RDP og DNS. Innleveringer: 8 obligatoriske øvinger Personlig veileder: ja Vurderingsform: 2 dagers praktisk hjemmeeskamen med både teoretiske og praktiske oppgaver. Ansvarlig: Stein Meisingseth Eksamensdato: 17.12.13 / 20.05.14         Læremål: KUNNSKAPER:Kandidaten skal:- kjenne til fordelen med å ta i bruk Citrix XenApp for en bedrift/organisasjon- kunne gjøre rede for hvordan Citrix XenApp brukes som publiseringsplattform- kunne beskrive Citrix XenApp brukes for å rulle ut applikasjoner- kunne gjøre rede for hvordan XenApp kan tas i bruk som applikasjonsvirtualisering på klientside (streaming) og på serverside (publishing)- kunne oppnå optimal applikasjonsytelse og fleksible leveransemuligheter FERDIGHETER:Kandidaten skal:- kunne installere Citrix XenApp- kunne sette opp administrativ konfigurasjon- kunne sette opp og publisere applikasjoner, innhold og desktops for brukere- kunne konfigurere applikasjoner for streaming til servere og til desktops- kunne vurdere hvilken sikkerhet som kreves- kunne sette opp og konfigurere overvåkning- kunne konfigurere og bruke et administrativt grensesnitt GENERELL KOMPETANSEKandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter i en bedrift som vil bruke Citrix XenApp- kan i et forklare og gjøre bruk av sin kunnskap for bruk av Citrix XenApp Innhold:- introduksjon til Citrix XenApp - installasjon av Citrix XenApp (6.5) - praktisk bruk - konfigurasjon - bruk av Web Interface - publisere applikasjoner og innhold - streame applikasjoner - sette opp restriksjoner - konfigurere lastbalansering - maksimere brukeropplevelse - bruke av skrivere - sikkerhet - overvåkningLes mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Citrix XenApp 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.   [-]

Elasticsearch [-]

AZ-400: Designing and Implementing Microsoft DevOps solutions [-]

Etter den fantastiske suksessen med Premiere Pro-klassen vår for nybegynnere, bestemte vi oss for å lage en oppfølging. Grundig produsert med tanke på en morsom og engasjerende læringsopplevelse. Kursmål Du vil lære alle funksjonene i Adobe Premiere Pro som lar deg gjøre følgende: Ulike redigeringsarbeidsflytteknikker Avanserte innstillinger og alternativer Jobber med snarveier Bildetekster og undertekster Lag egendefinerte forhåndsinnstillinger og maler Overgangsteknikker Stabiliser og reverser bevegelsesklipp Tidsomlegging Maskering og sporing Fargekorrigering og gradering Fikser og forbedrer lyd Arbeid med kodeker og gjengivelsesalternativer [-]

The course is designed for Azure system administrators, solutions architects, and SysOps administrators who are familiar with Azure features and setup and want to gain experience configuring Google Cloud products immediately.  This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud. Objectives This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto-scaling, load balancing, storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introducing Google Cloud -Explain the advantages of Google Cloud-Define the components of Google’s network infrastructure, including points of presence, data centers, regions, and zones-Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Module 2: Getting Started with Google Cloud -Identify the purpose of projects on Google Cloud-Understand how Azure’s resource hierarchy differs from Google Cloud’s-Understand the purpose of and use cases for Identity and Access Management-Understand how Azure AD differs from Google Cloud IAM-List the methods of interacting with Google Cloud-Launch a solution using Cloud Marketplace Module 3: Virtual Machines in the Cloud -Identify the purpose and use cases for Google Compute Engine-Understand the basics of networking in Google Cloud-Understand how Azure VPC differs from Google VPC-Understand the similarities and differences between Azure VM and Google Compute Engine-Understand how typical approaches to load-balancing in Google Cloud differ from those in AzureDeploy applications using Google Compute Engine Module 4: Storage in the Cloud -Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore-Understand how Azure Blob compares to Cloud Storage-Compare Google Cloud’s managed database services with Azure SQL-Learn how to choose among the various storage options on Google Cloud-Load data from Cloud Storage into BigQuery Module 5: Containers in the Cloud -Define the concept of a container and identify uses for containers-Identify the purpose of and use cases for Google Container Engine and Kubernetes-Understand how Azure Kubernetes Service differs from Google Kubernetes Engine-Provision a Kubernetes cluster using Kubernetes Engine-Deploy and manage Docker containers using kubectl Module 6: Applications in the Cloud -Understand the purpose of and use cases for Google App Engine-Contrast the App Engine Standard environment with the App Engine Flexible environment-Understand how App Engine differs from Azure App Service-Understand the purpose of and use cases for Google Cloud Endpoints Module 7: Developing, Deploying and Monitoring in the Cloud -Understand options for software developers to host their source code-Understand the purpose of template-based creation and management of resources-Understand how Cloud Deployment Manager differs from Azure Resource Manager-Understand the purpose of integrated monitoring, alerting, and debugging-Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics-Create a Deployment Manager deployment-Update a Deployment Manager deployment-View the load on a VM instance using Google Monitoring Module 8: Big Data and Machine Learning in the Cloud -Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms-Understand how Google Cloud BigQuery differs from Azure Data Lake-Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus-Understand how Google Cloud’s machine-learning APIs differ from Azure’s-Load data into BigQuery from Cloud Storage-Perform queries using BigQuery to gain insight into data Module 9: Summary and Review -Review the products that make up Google Cloud and remember how to choose among them-Understand next steps for training and certification-Understand, at a high level, the process of migrating from Azure to Google Cloud [-]

The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. After completing this course, students will be able to: Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics Course prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.Recommended prerequisites:M-DP900 - Microsoft Azure Data FundamentalsM-AZ900 - Microsoft Azure Fundamentals Agenda Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Module 16: Build reports using Power BI integration with Azure Synapase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Du må ha god kjennskap til Windows 2008 server, oppsett av AD og helst Exchange server Innleveringer: Øvinger: 8 må være godkjent.  Vurderingsform: 5 timer praktisk hjemmeeksamen med både teoretiske og praktiske oppgaver. Ansvarlig: Stein Meisingseth Eksamensdato: 09.12.13 / 12.05.14         Læremål: KUNNSKAPER:Kandidaten:- kjenner til bruken av skripting i forskjellige situasjoner i en bedrift/organisasjon- kjenner til forskjellige skripspråk- kan gjøre rede for hvordan skripting kan automatisere oppgaver i en driftssituasjon- kan bruke PowerShell for å automatisere driftsoppgaver i Windows server, VMware og andre driftsmiljøer FERDIGHETER:Kandidaten:- Powershell - historie- kan vise hvordan er PowerShell bygd opp- kan bruke PowerShell i Windows server- kan lage kommandoer og scripts i Powershell- PowerShell og .NET- kan bruke av PowerShell i Active Directory- kan bruke av PowerShell i VMware- kan bruke PowerShell i Exchange GENERELL KOMPETANSE:Kandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter i en bedrift som vil automatisere typiske driftsoppgaver Innhold:- introduksjon til PowerShell 2 og 3 - hvordan lage script i PowerShell - kommandoer i PowerShell - forenkling og automatisering av drift av Windows OS med PowerShell - forenkling og automatisering av drift av Windows server med PowerShell - forenkling og automatisering av drift av Exchange server med PowerShell - forenkling og automatisering av drift av VMware med PowerShellLes mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Powershell i praktisk scripting 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

Security Engineering on AWS [-]

Dette kurset tar for seg alle de beregningsfunksjoner som ligger i MagiCAD i tillegg til noen funksjoner i NTI TOOLS og Revit forøvrig. Beregninger utføres på et «ferdig» prosjektert anlegg, det er lite fokus på prosjektering. Av beregningsfunksjoner hører: samtidighet i vannførende systemer, VAV på ventilasjon, dimensjonering av rør og kanaler, trykkfall og innregulering, differensetrykkregulering på varmeanlegg, lydberegninger i kanalnett og totallyd i rom. I tillegg gjennomgås funksjoner for analyse og presentasjon av beregningene for bedre kvalitetssikring av modellene. Hovedpunkter: Dette er noen av temaene som gjennomgås på kurset: Luftmengder i rom Beregninger - Spillvann Beregninger - KV – VV – VVC Beregninger – Varmeanlegg Beregninger – Sprinkleranlegg (ved behov) Beregninger - Ventilasjonsanlegg Lydberegninger i kanalnett Lydberegninger i rom Temperatur i kanalnett ved branntilfelle Grafiske analyser [-]

Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring. Course Objectives This course teaches participants the following skills: Configure VPC networks and virtual machines Administer Identity and Access Management for resources Implement data storage services in Google Cloud Manage and examine billing of Google Cloud resources Monitor resources using Google Cloud services Connect your infrastructure to Google Cloud Configure load balancers and autoscaling for VM instances Automate the deployment of Google Cloud infrastructure services Leverage managed services in Google Cloud All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introduction to Google Cloud -List the different ways of interacting with Google Cloud-Use the Cloud Console and Cloud Shell-Create Cloud Storage buckets-Use the Google Cloud Marketplace to deploy solutions Module 2: Virtual Networks -List the VPC objects in Google Cloud-Differentiate between the different types of VPC networks-Implement VPC networks and firewall rules-Implement Private Google Access and Cloud NAT Module 3: Virtual Machines -Recall the CPU and memory options for virtual machines-Describe the disk options for virtual machines-Explain VM pricing and discounts-Use Compute Engine to create and customize VM instances Module 4: Cloud IAM -Describe the Cloud IAM resource hierarchy-Explain the different types of IAM roles-Recall the different types of IAM members-Implement access control for resources using Cloud IAM Module 5: Data Storage Services -Differentiate between Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Firestore and Cloud Bigtable-Choose a data storage service based on your requirements-Implement data storage services Module 6: Resource Management -Describe the cloud resource manager hierarchy-Recognize how quotas protect Google Cloud customers-Use labels to organize resources-Explain the behavior of budget alerts in Google Cloud-Examine billing data with BigQuery Module 7: Resource Monitoring -Describe the services for monitoring, logging, error reporting, tracing, and debugging-Create charts, alerts, and uptime checks for resources with Cloud Monitoring-Use Cloud Debugger to identify and fix errors Module 8: Interconnecting Networks -Recall the Google Cloud interconnect and peering services available to connect your infrastructure to Google Cloud-Determine which Google Cloud interconnect or peering service to use in specific circumstances-Create and configure VPN gateways-Recall when to use Shared VPC and when to use VPC Network Peering Module 9: Load Balancing and Autoscaling -Recall the various load balancing services-Determine which Google Cloud load balancer to use in specific circumstances-Describe autoscaling behavior-Configure load balancers and autoscaling Module 10: Infrastructure Modernization -Automate the deployment of Google Cloud services using Deployment Manager or Terraform-Outline the Google Cloud Marketplace Module 11: Managed Services Describe the managed services for data processing in Google Cloud [-]

Hvem passer kurset for? Deg som lager presentasjoner eller presenterer/markedsfører innhold på nett. Forhåndskunnskap: Kurset llustrator innføring eller tilsvarende kunnskap Dette lærer du: Teknikker til tegning av enkle figurer og former til bruk i illustrasjonen Bruk av tall i diagrammer Tilpasning av diagrammets utseende Fargebruk Teknikker for å hente inn nye idéer https://igm.no/infografikk/ [-]

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

Ønsker du å jobbe med ulike tegninger i Visio, men føler du ikke mestrer programmet? Vil du i tillegg kunne lage egne maler for å jobbe mer effektivt? Da er ”Visio Grunnleggende” kurset for deg! Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1    Hva er Visio? Få oversikt. Bli kjent med programvinduet og hvordan du kan tilpasse det etter dine behov. Mal. Hvordan er en mal bygd opp og hvordan jobbe med en tegning? Formatering. Lær å formatere og hva formateringsbegrepet betyr. Sjablonger og figurer. Hva er sjablonger og figurer?   Å jobbe effektivt med Visio Bygge opp en tegning. Lær å bygge opp en tegning fra bunnen av. Hurtigtaster. Effektiv bruk av tastatur og mus. Formatering. Bruk formatering for å gjøre tegningene oversiktlige og informasjonen mest mulig tilgjengelig. Ark. Lær å jobbe med flere ark, navngi dem, slette dem, bruke bakgrunner etc. Praktisk oppgaveløsing. Jobb med skreddersydde oppgaver innenfor dagens temaer. Andre Office-programmer. Lær å bruke Visio-tegninger i andre Office-programmer.   Flytskjema og organisasjonskart Koblinger. Lær å koble figurer på en effektiv måte. Oppsett. Hvordan sørge for at figurene står plassert på en nøyaktig og oversiktlig måte? Navigasjon. Bygge opp praktisk navigasjon mellom sidene i en større tegning.   Dag 2    Nettverksdiagram Figurdata. Knytt praktisk informasjon til figurene i tegningen. Rapporter. Hvordan hente ut rapporter fra en tegning?   Prosjektplaner Tidslinje. Illustrere faser i et prosjekt på en oversiktlig måte. Gantt-diagram. Vise prosjektinformasjon på en mer detaljert måte. Utskrift. Få oversikt over de vanligste problemstillingene ved utskrift.   Egne maler Maler. Hva er maler, deres styrke og hvordan kan jeg utnytte dem best mulig i mitt arbeid? Sjablonger. Bygge opp en egen samling med de figurene du skal bruke. Figurer. Lær å lage egne tilpassede figurer. Praktisk oppgaveløsing. Jobb med skreddersydde oppgaver innenfor dagens temaer.   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

Oracle BI Publisher: Fundamentals [-]

 Students will learn through a mix of demonstrations and hands-on lab experiences deploying virtual desktop experiences and apps on Windows Virtual Desktop and optimizing them to run in multi-session virtual environments.Students for AZ-140: Configuring and Operating Windows Virtual Desktop on Microsoft Azure are interested in delivering applications on Windows Virtual Desktop and optimizing them to run in multi-session virtual environments. As a Windows Virtual Desktop administrator, you will closely with the Azure Administrators and Architects, along with Microsoft 365 Administrators. Windows Virtual Desktop administrator responsibilities include planning, deploying, packaging, updating, and maintaining the Azure Windows Virtual Desktop infrastructure. They also create session host images, implement and manage FSLogix, monitor Windows Virtual Desktop performance, and automate Windows Virtual Desktop management tasks. COURSE OBJECTIVES   Select an appropriate licensing model for Windows Virtual Desktop Implement networking for Windows Virtual Desktop Manage Windows Virtual Desktop session hosts by using Azure Bastion Configure storage for FSLogix components Create and manage session host images Implement Azure roles and role-based access control (RBAC) for Windows Virtual Desktop Configure user Windows Virtual Desktop experience settings Install and configure apps on a session host Implement business continuity and disaster recovery Monitor and manage Windows Virtual Desktop performance     COURSE CONTENT Module 1: Plan a Windows Virtual Desktop Architecture In this module, you will learn how to assess existing physical and virtual desktop environments, plan and configure name resolution for Active Directory (AD) and Azure Active Directory Domain Services (Azure AD DS), and plan for Windows Virtual Desktop client deployments. LESSONS M1 Windows Virtual Desktop Architecture Design the WVD architecture Design for user identities and profiles LAB: PREPARE FOR DEPLOYMENT OF AZURE WINDOWS VIRTUAL DESKTOP (AZURE AD DS) LAB: PREPARE FOR DEPLOYMENT OF AZURE WINDOWS VIRTUAL DESKTOP (AD DS) After completing module 1, students will be able to: Understand Windows Virtual Desktop Components Understand personal and pooled desktops Recommend an operating system for a WVD implementation Plan a host pools architecture Module 2: Implement a WVD Infrastructure In this module, you will learn how to manage connectivity to the internet and on-premises networks, create a host pool by using the Azure portal, deploy host pools and hosts by using Azure Resource Manager templates, apply OS and application updates to a running WVD host, and create a master image. LESSONS M2 Implement and manage networking for WVD Implement and manage storage for WVD Create and configure host pools and session hosts Create and manage session host image LAB: CREATE AND CONFIGURE HOST POOLS AND SESSION HOSTS (AZURE AD DS) LAB: DEPLOY HOST POOLS AND SESSION HOSTS BY USING THE AZURE PORTAL (AD DS) LAB: IMPLEMENT AND MANAGE STORAGE FOR WVD (AZURE AD DS) LAB: DEPLOY HOST POOLS AND HOSTS BY USING AZURE RESOURCE MANAGER TEMPLATES LAB: DEPLOY AND MANAGE HOST POOLS AND HOSTS BY USING POWERSHELL After completing module 2, students will be able to: Implement Azure virtual network connectivity Manage connectivity to the internet and on-premises networks Understanding Windows Virtual Desktop network connectivity Configure WVD session hosts using Azure Bastion Configure storage for FSLogix components Configure disks and file shares Modify a session host image Create and use a Shared Image Gallery (SIG) Module 3: Manage Access and Security In this module, you will learn how to plan and implement Azure roles and RBAC for WVD, implement Conditional Access policies for connections, plan and implement MFA, and manage security by using Azure Security Center. LESSONS M3 Manage access Manage security LAB: CONFIGURE CONDITIONAL ACCESS POLICIES FOR CONNECTIONS TO WVD (AD DS) After completing module 3, students will be able to: Manage local roles, groups and rights assignment on WVD session hosts. Configure user restrictions by using AD group policies and Azure AD policies Understand Conditional Access policy components Prepare for Azure Active Directory (Azure AD)-based Conditional Access for Windows Virtual Desktop Implement Azure AD-based Conditional Access for Windows Virtual Desktop Module 4: Manage User Environments and Apps In this module, you will learn how to plan for FSLogix, install FSLogix, configure Cloud Cache, deploy an application as a RemoteApp, and implement and manage OneDrive for Business for a multi-session environment. LESSONS M4 Implement and manage FSLogix Configure user experience settings Install and configure apps on a session host LAB: WINDOWS VIRTUAL DESKTOP PROFILE MANAGEMENT (AZURE AD DS) LAB: WINDOWS VIRTUAL DESKTOP PROFILE MANAGEMENT (AD DS) LAB: WINDOWS VIRTUAL DESKTOP APPLICATION PACKAGING (AD DS) After completing module 4, students will be able to: Configure Profile Containers Configure Azure Files to store profile containers for WVD in an AAD DS environment Implement FSLogix based profiles for Windows Virtual Desktop in Azure AD DS environment Implement FSLogix based profiles for Windows Virtual Desktop Prepare for and create MSIX app packages Implement MSIX app attach container for Windows Virtual Desktop in AD DS environmen Module 5: Monitor and maintain a WVD infrastructure In this module, you will learn how to plan and implement a disaster recovery plan for WVD, configure automation for WVD, implement autoscaling in host pools, and optimize session host capacity and performance. LESSONS M5 Plan and implement business continuity and disaster recovery Automate WVD management tasks Monitor and manage performance and health LAB: IMPLEMENT AUTOSCALING IN HOST POOLS (AD DS) After completing module 5, students will be able to: Plan and implement a disaster recovery plan for WVD Configure automation for WVD Monitor WVD by using Azure Monitor Customize Azure Workbooks for WVD monitoring Configure autoscaling of Windows Virtual Desktop session hosts Verify autoscaling of Windows Virtual Desktop session host [-]