Oversikt over relevante kurs innen IT-kurs i Aust-Agder

Du vil få tilsendt en «Core guidance» bok og sertifiserings-voucher slik at du kan ta sertifiseringstesten for eksempel hjemme eller på jobb. Denne vil være gyldig i ett år. Tid for sertifiseringstest avtales som beskrevet i e-post med voucher. Eksamen overvåkes av en web-basert eksamensvakt.   Eksamen er på engelsk. Eksamensformen er multiple choice - 50 spørsmål skal besvares, og du består ved 50% korrekte svar (dvs 25 av 50 spørsmål). Deltakerne har 40 minutter til rådighet på eksamen.  Ingen hjelpemidler er tillatt.   Nødvendige forkunnskaper: Ingen [-]

. This course includes identity content for Azure AD, enterprise application registration, conditional access, identity governance, and other identity tools.   TARGET AUDIENCE This course is for the Identity and Access Administrators who are planning to take the associated certification exam, or who are performing identity and access administration tasks in their day-to-day job. This course would also be helpful to an administrator or engineer that wants to specialize in providing identity solutions and access management systems for Azure-based solutions; playing an integral role in protecting an organization. COURSE OBJECTIVES Implement an identity management solution Implement an authentication and access management solutions Implement access management for apps Plan and implement an identity governancy strategy COURSE CONTENT Module 1: Implement an identity management solution Learn to create and manage your initial Azure Active Directory (Azure AD) implementation and configure the users, groups, and external identities you will use to run your solution. Lessons M1 Implement Initial configuration of Azure AD Create, configure, and manage identities Implement and manage external identities Implement and manage hybrid identity Lab 1a: Manage user roles Lab 1b: Setting tenant-wide properties Lab 1c: Assign licenses to users Lab 1d: Restore or remove deleted users Lab 1e: Add groups in Azure AD Lab 1f: Change group license assignments Lab 1g: Change user license assignments Lab 1h: Configure external collaboration Lab 1i: Add guest users to the directory Lab 1j: Explore dynamic groups After completing module 1, students will be able to: Deploy an initail Azure AD with custom settings Manage both internal and external identities Implement a hybrid identity solution Module 2: Implement an authentication and access management solution Implement and administer your access management using Azure AD. Use MFA, conditional access, and identity protection to manager your identity solution. Lessons M2 Secure Azure AD user with MFA Manage user authentication Plan, implement, and administer conditional access Manage Azure AD identity protection Lab 2a: Enable Azure AD MFA Lab 2b: Configure and deploy self-service password reset (SSPR) Lab 2c: Work with security defaults Lab 2d: Implement conditional access policies, roles, and assignments Lab 2e: Configure authentication session controls Lab 2f: Manage Azure AD smart lockout values Lab 2g: Enable sign-in risk policy Lab 2h: Configure Azure AD MFA authentication registration policy After completing module 2, students will be able to: Configure and manage user authentication including MFA Control access to resources using conditional access Use Azure AD Identity Protection to protect your organization Module 3: Implement access management for Apps Explore how applications can and should be added to your identity and access solution with application registration in Azure AD. Lessons M3 Plan and design the integration of enterprise for SSO Implement and monitor the integration of enterprise apps for SSO Implement app registration Lab 3a: Implement access management for apps Lab 3b: Create a custom role to management app registration Lab 3c: Register an application Lab 3d: Grant tenant-wide admin consent to an application Lab 3e: Add app roles to applications and recieve tokens After completing module 3, students will be able to: Register a new application to your Azure AD Plan and implement SSO for enterprise application Monitor and maintain enterprise applications Module 4: Plan and implement an identity governancy strategy Design and implement identity governance for your identity solution using entitlement, access reviews, privileged access, and monitoring your Azure Active Directory (Azure AD). Lessons M4 Plan and implement entitlement management Plan, implement, and manage access reviews Plan and implement privileged access Monitor and maintain Azure AD Lab 4a: Creat and manage a resource catalog with Azure AD entitlement Lab 4b: Add terms of use acceptance report Lab 4c: Manage the lifecycle of external users with Azure AD identity governance Lab 4d: Create access reviews for groups and apps Lab 4e: Configure PIM for Azure AD roles Lab 4f: Assign Azure AD role in PIM Lab 4g: Assign Azure resource roles in PIM Lab 4h: Connect data from Azure AD to Azure Sentinel After completing module 4, students will be able to: Mange and maintain Azure AD from creation to solution Use access reviews to maintain your Azure AD Grant access to users with entitlement management [-]

Bli en ekspert i verdens ledende programvare for digital bildebehandling og grafisk design med kurset "Photoshop: Komplett". Ledet av sertifisert Photoshop-ekspert Espen Faugstad hos Utdannet.no, er dette kurset perfekt for alle som ønsker å utforske og mestre Adobe Photoshop, et verktøy sentralt i nesten alle kreative prosjekter. Dette omfattende kurset tar deg gjennom alle aspekter av Photoshop, fra grunnleggende til avanserte teknikker. Du vil lære alt fra å åpne og håndtere dokumenter, jobbe med lag, utføre markeringer og beskjæringer, til avansert retusjering og redigering. Kurset dekker også bruk av justeringer, masker, effekter, blend modes og filtre. Med praktiske prosjekter og eksempler vil du utvikle ferdigheter som gjør deg i stand til å løse komplekse og kreative utfordringer, og ved kursets slutt vil du ha oppnådd en dyptgående forståelse og kompetanse i Photoshop. Dette kurset vil utruste deg med kunnskapen og ferdighetene som trengs for å utnytte Photoshop i full skala, enten for personlig bruk eller i en profesjonell sammenheng.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Åpne Kapittel 3: Dokument Kapittel 4: Image Kapittel 5: Layers Kapittel 6: Markere Kapittel 7: Beskjære Kapittel 8: Retusjere Kapittel 9: Verktøy Kapittel 10: Adjustments Kapittel 11: Masker Kapittel 12: Effekter Kapittel 13: Blend Modes Kapittel 14: Filter Kapittel 15: Prosjekter Kapittel 16: Eksportere Kapittel 17: Avslutning   Varighet: 8 timer og 59 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Tjenesten fungerer på samme måte som strømmetjenester for musikk eller TV-serier. Våre kunder betaler en fast månedspris og får tilgang til alle kursene som er produsert så langt. Plattformen har hatt en god vekst de siste årene og kan skilte med 30.000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling moro, spennende og tilgjengelig for alle – og med oss har vi Innovasjon Norge og Forskningsrådet. [-]

Objectives Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Understand how pod networking works in Google Kubernetes Engine Create and manage Kubernetes Engine clusters using the Google Cloud Console and gcloud/kubectl commands   Course Outline Module 1: Introduction to Google Cloud -Use the Google Cloud Console-Use Cloud Shell-Define Cloud Computing-Identify Google Cloud compute services-Understand Regions and Zones-Understand the Cloud Resource Hierarchy-Administer your Google Cloud Resources Module 2: Containers and Kubernetes in Google Cloud -Create a Container Using Cloud Build-Store a Container in Container Registry-Understand the Relationship Between Kubernetes and Google Kubernetes Engine (GKE)-Understand how to Choose Among Google Cloud Compute Platforms Module 3: Kubernetes Architecture -Understand the Architecture of Kubernetes: Pods, Namespaces-Understand the Control-plane Components of Kubernetes-Create Container Images using Cloud Build-Store Container Images in Container Registry-Create a Kubernetes Engine Cluster Module 4: Introduction to Kubernetes Workloads -The kubectl Command-Introduction to Deployments-Pod Networking-Volumes Overview [-]

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. [-]

Docker and Kubernetes Development [-]

Excel for Controllere og Økonomisjefer [-]

ISO 27032 Lead Cybersecurity Manager [-]

• Final Cut grensesnitt & funksjoner oversikt som: Fordeler av “magnetic timeline”, “connected clips & secondary storyline”, lyd og “roles”• Final Cut keyboard shortcuts• Import og organisasjon av videofiler i “library” med “keywords”• Klipp av en videoreportasje med innklippsbilder, intervju, voiceover og logo/ grafikk• Sync av ekstern lyd• Flerkameraklipping med “Multicam”• Fargekorrigering• Lydmiks og lydforbedring• Enkle “Film looks” effekter og justering av effekter• 2D og 3D tekst, legge på navn og tittel, enkel keyframeing & animasjon av logo og grafikk• Eksport Dag 2: Fordypning i FCPX og Motion 5 for å bygge et sett av animasjoner og grafikk for lynrask produksjon av et TV-program / YouTube video-serie • Avanserte video- og grafikk-komposisjoner med flere lag• Triks til å overkomme begrensningene i “magnetic timeline”• Anonymisering av ansikter og nummerskilt• Motion: Tilpassning av FCPX “Transitions” og “Titles” i Motion 5 for å skape egne design på en enkel måte• Motion 5: 2D animasjoner og tekst tracking• Motion 5: Enkle 3D animasjoner og kamera• Motion 5: Keyframes og Behaviors• Motion 5: Vi kombinerer alt vi lærer om Motion 5 og skaper grafiske elementer for et TV-program / YouTube video-serie som logo-intro-animasjon, lower-third, custom transitions/logo stinger.• Motion 5: Publisering til FCPX for lynrask produksjon i framtiden [-]

DP-080: Querying Data with Microsoft Transact-SQL [-]

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

AI-050: Develop Generative AI Solutions with Azure OpenAI Service [-]

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. [-]

Studieår: 2013-2014   Gjennomføring: Høst Antall studiepoeng: 5.0 Forutsetninger: Erfaring fra et objektorientert programmeringsspråk, kjennskap til prosjektarbeid Innleveringer: Innleverte øvinger. Det blir gitt 10 øvinger, 8 må være godkjent for å kunne gå opp til eksamen. Personlig veileder: ja Vurderingsform: 4 timer skriftlig eksamen. Ansvarlig: Tore Berg Hansen Eksamensdato: 12.12.13         Læremål: Forventet læringsutbytte:Etter å ha gjennomført emnet Objektorientert systemutvikling skal studenten ha følgende samlete læringsutbytte: KUNNSKAPER:Kandidaten:- kan definere, gjenkjenne og forklare de grunnleggende konsepter for utvikling av store programvaresystemer basert på det objektorienterte paradigme- argumentere for betydningen av å følge en prosessmodell- argumentere for fordelene med smidige prosesser- argumentere for modellbasert utvikling- beskrive modellene som brukes i objektorientert systemutvikling og hvordan de henger sammen- forklare begrepene arkitektoniske stiler og designmønstre FERDIGHETER:Kandidaten:- kan demonstrere den systematiske gangen fra krav, via arkitektonisk og detaljert design, til ferdig kodet og implementert system GENERELL KOMPETANSE:Kandidaten:- er klar over at utvikling av store programvaresystemer er ingeniørarbeid- er seg bevisst at utvikling av komplekse programvaresystemer krever koordinert innsats av et velfungerende team som følger en definert, smidig prosess- er opptatt av tett kontakt med alle interessenter for å oppnå et godt resultat Innhold:Utviklingsprosesser. Modellering. UML. Verktøy. Objektorientert analyse Objektorientert design. Bruk av arkitektoniske stiler og design mønstre. Implementasjon og test.Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Dette faget går: Høst 2013    Fag Objektorientert systemutvikling 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

  Fleksible kurs for fremtidenNy 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.   Navisworks grunnkurs   Her er et utvalg av temaene du vil lære på kurset: forstå hvordan tverrfaglige modeller settes sammen analysere modellen gjennom visualisering og navigering håndtering av objekter sette inn målsetting legg inn snitt finne informasjon på objektene Navisworks håndterer et stort antall filformater og det er viktig å forstå hvordan tverrfaglige modeller settes sammen slik at dette muligjør analyse av modellen gjennom visualisering, navigering, håndtering av objekter, sette inn målsetting, legge inn snitt og finne informasjon på objektene.   Tilpassete kurs for bedrifterVi 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 [-]