Kurs i Ådalsbruk

Spesialseminar 2: «Generasjonsskifter - utfordringer og løsninger»    Dette spesialseminaret er åpent og kostnadsfritt for alle som er med i styrenettverksgrupper arrangert av Styreforeningen. For andre deltakere som er medlemmer av Styreforeningen koster seminaret kr. 4.990,-.For deltakere som ikke er med i styrenettverksgrupper og som ikke er medlemmer av Styreforeningen er prisen kr. 5.990,-   Seminaret tar for seg en rekke krevende faser og situasjoner som kan oppstå i forbindelse med styrearbeidet. Vi ser blant annet på:   hva undersøkeler som er gjort omkring generasjonsskifteprosesser forteller oss uventet aksjonær bortgang og ulike utfordringer det kan medføre fremtidsfullmakt i forbindelse med aksjeeierskap og aksjeovertakels viktigheten av vedtektsbestemmelser eventuelt aksjonæravtaler ved generasjonsskifter, og utfordringene som kan oppstå dersom situasjonen ikke er hensynttat i formalia styrets rolle i generasjonsskifteprosesser forberedelsene og tilretteleggingen i generasjonsskifteprosesser sjekkliste ved generasjonsskifteprosesser [-]

I Matematikk R2 lærer du om integralregning, rekker, vektorer og trigonometri. Matematikk R2 er for deg som trenger realfagmatematikk for videre studier eller for å forbedre karakteren din. Faget er obligatorisk om du skal studere til ingeniør eller arkitekt. Matematikk R2 gir 1 realfagpoeng. Du må ha matematikk R1 for å ta dette faget. Gjennomføring NettstudierDu bestemmer hvor og når du vil lære. Her får du varierte leksjoner i form av tekster, video, quiz, podcast, veiledning og oppgaver. Du har alltid kontakt med din personlige lærer hos K2. Målet er å gjøre deg best mulig forberedt til eksamen. Eksamen Eksamen i Matematikk R2 er skriftlig. Som privatist må du selv melde deg opp til eksamen. Oppmeldingsfristene er normalt 15. september og 1. februar. Husk at betaling av eksamensavgiften skjer ved oppmelding. Veien videre Om du har generell studiekompetanse (GENS) og velger å ta fagene fysikk 1 og matematikk R1 og R2 som privatist, da oppfyller du opptakskravene til flere studier, inkludert ingeniørstudier. Se praktisk info for frister og opptak til universitet og høyskole. Gratis veiledning Er du usikker på hva som skal til for å få studiekompetanse, ta gjerne kontakt med oss for gratis veiledning. Vi har veiledere med mange års erfaring som står klare til å hjelpe deg!Ønsker du mer informasjon om kurset velg "Send meg info"-knappen under. Vil du chatte med oss, så klikk på ikonet nederst i høyre hjørne. Gratis veiledning Vi har veiledere med mange års erfaring som står klare til å hjelpe deg! Er du usikker på hva som skal til for å få studiekompetanse, ta gjerne kontakt med oss for gratis veiledning.  Ønsker du mer informasjon om kurset velg "Send meg info"-knappen under. Vil du chatte med oss, klikk på ikonet nederst i høyre hjørne. Lånekassestøtte Utdanningen er godkjent i lånekassen. Du søker direkte via lanekassen.no. Alt du må vite om lån og stipend fra Lånekassen som deltaker hos K2 utdanning Støtteordning Er du organisert i en fagforening, kan du i de fleste fagforeningene søke støtte til utdanning. Dersom du er organisert bør du sjekke med din fagforening om muligheter for støtte, frister og hvordan du søker. Forkunnskaper Du må ha fullført grunnskole eller tilsvarende opplæring. Minoritetsspråklige bør ha minimum B1-nivå i norsk muntlig og skriftlig. Dersom du har behov for å lære mere norsk før du starter på utdanning har vi norskkurs på forskjellig nivå (A1-B2). Språkkursene er digitale med personlig oppfølging fra lærer. Se alle norskkurs K2 tilbyr. Krav til utstyr Som deltaker hos K2 må du ha tilgang til pc på eksamen. I tillegg trenger du PC-versjonen av Office eller tilsvarende programmer. Se hva du har tilgang til av nettbaserte ressurser på eksamen. Praktisk info Du finner svar på ofte stilte spørsmål på nettsiden vår under praktisk info.     [-]

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.   [-]

Understand the purpose and key concepts of the Service Desk practice, including how it serves as the central point of contact between the service provider and the users, facilitating effective communication. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content mobil-optimised practical exercises     Exam: 20 questions Multiple Choice 30 minutes Closed book Minimum required score to pass: (65%)   [-]

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

MÅL:Etter kurset skal deltakerne kunne demonstrere kompetanse gitt i STCW kodens tabell A-VI/2-1.FREKVENS:Gyldig i 5 år.MYNDIGHETSKRAV:Kurset tilfredsstiller gjeldende emneplan utgitt av Sjøfartsdirektoratet ihht. STCW 78 konvensjonens regel VI/2, STCW kodens avsnitt A-VI/2 og tabell A-VI/2-1. Redningsfarkoster og mann-over-bord-båter, unntatt hurtiggående mann-over-bord-båter.INNHOLD:Kurset inneholder obligatoriske minstekrav til opplæring av redningsfarkost mann over bord båt personell i henhold til STCW konvensjonen og STCW koden. Ta kommando over en redningsfarkost eller mann over bord båt under og etter utsetting (teori og praksis).Betjene motor på en redningsfarkost (praktisk demonstrasjon).Håndtere overlevende og redningsfarkost etter evakuering av skipet (teori og praksis).Bruke innretninger til å angi posisjon, herunder kommunikasjons- og signalutstyr og lys- og røyksignaler (teori og praktisk demo).Gi førstehjelp til overlevende (teori og praksis). [-]

COURSE OVERVIEW Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. 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. TARGET AUDIENCE The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure. COURSE OBJECTIVES   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 CONTENT 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. Introduction to Azure Synapse Analytics Describe Azure Databricks Introduction to Azure Data Lake storage Describe Delta Lake architecture Work with data streams by using Azure Stream Analytics Lab 1: Explore compute and storage options for data engineering workloads Combine streaming and batch processing with a single pipeline Organize the data lake into levels of file transformation Index data lake storage for query and workload acceleration After completing module 1, students will be able to: Describe Azure Synapse Analytics Describe Azure Databricks Describe Azure Data Lake storage Describe Delta Lake architecture Describe Azure Stream Analytics 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. Design a multidimensional schema to optimize analytical workloads Code-free transformation at scale with Azure Data Factory Populate slowly changing dimensions in Azure Synapse Analytics pipelines Lab 2: Designing and Implementing the Serving Layer Design a star schema for analytical workloads Populate slowly changing dimensions with Azure Data Factory and mapping data flows After completing module 2, students will be able to: Design a star schema for analytical workloads Populate a slowly changing dimensions with Azure Data Factory and mapping data flows 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. Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Lab 3: Data engineering considerations Managing files in an Azure data lake Securing files stored in an Azure data lake After completing module 3, students will be able to: Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics 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). Explore Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Lab 4: Run interactive queries using serverless SQL pools Query Parquet data with serverless SQL pools Create external tables for Parquet and CSV files Create views with serverless SQL pools Secure access to data in a data lake when using serverless SQL pools Configure data lake security using Role-Based Access Control (RBAC) and Access Control List After completing module 4, students will be able to: Understand Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools 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. Understand big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Lab 5: Explore, transform, and load data into the Data Warehouse using Apache Spark Perform Data Exploration in Synapse Studio Ingest data with Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Spark pools in Azure Synapse Analytics Integrate SQL and Spark pools in Azure Synapse Analytics After completing module 5, students will be able to: Describe big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics 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. Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Lab 6: Data Exploration and Transformation in Azure Databricks Use DataFrames in Azure Databricks to explore and filter data Cache a DataFrame for faster subsequent queries Remove duplicate data Manipulate date/time values Remove and rename DataFrame columns Aggregate data stored in a DataFrame After completing module 6, students will be able to: Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks 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. Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Lab 7: Ingest and load Data into the Data Warehouse Perform petabyte-scale ingestion with Azure Synapse Pipelines Import data with PolyBase and COPY using T-SQL Use data loading best practices in Azure Synapse Analytics After completing module 7, students will be able to: Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory 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. Data integration with Azure Data Factory or Azure Synapse Pipelines Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines Lab 8: Transform Data with Azure Data Factory or Azure Synapse Pipelines Execute code-free transformations at scale with Azure Synapse Pipelines Create data pipeline to import poorly formatted CSV files Create Mapping Data Flows After completing module 8, students will be able to: Perform data integration with Azure Data Factory Perform code-free transformation at scale with Azure Data Factory 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. Orchestrate data movement and transformation in Azure Data Factory Lab 9: Orchestrate data movement and transformation in Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines After completing module 9, students will be able to: Orchestrate data movement and transformation 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. Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Lab 10: Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Understand developer features of Azure Synapse Analytics Optimize data warehouse query performance in Azure Synapse Analytics Improve query performance After completing module 10, students will be able to: Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics 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. Analyze and optimize data warehouse storage in Azure Synapse Analytics Lab 11: Analyze and Optimize Data Warehouse Storage Check for skewed data and space usage Understand column store storage details Study the impact of materialized views Explore rules for minimally logged operations After completing module 11, students will be able to: Analyze and optimize data warehouse storage in Azure Synapse Analytics 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. Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark pools Query Azure Cosmos DB with serverless SQL pools Lab 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Synapse Analytics Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics After completing module 12, students will be able to: Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics 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. Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Lab 13: End-to-end security with Azure Synapse Analytics Secure Azure Synapse Analytics supporting infrastructure Secure the Azure Synapse Analytics workspace and managed services Secure Azure Synapse Analytics workspace data After completing module 13, students will be able to: Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data 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. Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Lab 14: Real-time Stream Processing with Stream Analytics Use Stream Analytics to process real-time data from Event Hubs Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics Scale the Azure Stream Analytics job to increase throughput through partitioning Repartition the stream input to optimize parallelization After completing module 14, students will be able to: Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics 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. Process streaming data with Azure Databricks structured streaming Lab 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks Explore key features and uses of Structured Streaming Stream data from a file and write it out to a distributed file system Use sliding windows to aggregate over chunks of data rather than all data Apply watermarking to remove stale data Connect to Event Hubs read and write streams After completing module 15, students will be able to: Process streaming data with Azure Databricks structured streaming Module 16: Build reports using Power BI integration with Azure Synpase 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. Create reports with Power BI using its integration with Azure Synapse Analytics Lab 16: Build reports using Power BI integration with Azure Synpase Analytics Integrate an Azure Synapse workspace and Power BI Optimize integration with Power BI Improve query performance with materialized views and result-set caching Visualize data with SQL serverless and create a Power BI report After completing module 16, students will be able to: Create reports with Power BI using its integration with Azure Synapse Analytics 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. Use the integrated machine learning process in Azure Synapse Analytics Lab 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics Create an Azure Machine Learning linked service Trigger an Auto ML experiment using data from a Spark table Enrich data using trained models Serve prediction results using Power BI After completing module 17, students will be able to: Use the integrated machine learning process in Azure Synapse Analytics     [-]

The Practitioner is the second of two examinations that you are required to pass to become a Registered PRINCE2 Practitioner. The examination measures whether a candidate can demonstrate sufficient ability to apply and tailor PRINCE2 to the running and managing of a project. A successful Practitioner candidate should, with suitable direction, be able to start applying the method to a real project.  PRINCE2 themes Business case Organisation Plans Risk Quality Change Progress Plus activity-based case study Processes All PRINCE2® Practitioner Online courses on this page are offered by ILX Group an ATO of AXELOS Limited. PRINCE2® is a registered trade mark of AXELOS Limited, used under permission of AXELOS Limited. All rights reserved.   Learning outcomes By the end of the PRINCE2 Practitioner e-learning course you should be able to: *Apply the PRINCE2 principles in context*Apply and tailor relevant aspects of PRINCE2 themes in context*Apply and tailor relevant aspects of PRINCE2 processes in context Course overview Processes:*Starting up a project*Initiating a project*Controlling a stage*Managing product delivery*Managing a stage boundary*Directing a project*Closing a project*PRINCE2 walkthrough * PRINCE2 Practitioner exam simulator* Practitioner sample papers Also includes...* The PRINCE2 template manager- A comprehensive collection of document templates to kick-start your implementation of PRINCE2* Glossary of terms * Frequently asked questions* Training guide to assist you with your study* Exam style questions and rationale Target audience Project managers and aspiring project managersIt is also relevant to other key staff involved in the design, development and delivery of projects, including:*Project board members (e.g. senior responsible owners)*Team managers (e.g. product delivery managers)*Project assurance (e.g. business change analysts)*Project support (e.g. project and programme office personnel)*Operational line managers/staff Pre-requisites In order to sit the PRINCE2 Practitioner examination you must provide proof of having passed one of the following: *PRINCE2 Foundation*Project Management Professional (PMP)®*Certified Associate in Project Management (CAPM)®*IPMA Level A (Certified Projects Director)*IPMA Level B® (Certified Senior Project Manager)*IPMA Level C® (Certified Project Manager)*IPMA Level D® (Certified Project Management Associate) Only current certifications will qualify as a pre-requisite What's included? * 12 months online access to our accredited PRINCE2 Practitioner course* PRINCE2 Practitioner exam: valid for 12 months from purchase date. Exam must be taken online via remote proctor* Full tutor support, plus many additional resources to help put PRINCE2 into practice* PRINCE2 Practitioner exam simulator* PRINCE2 process map   Exam format The format of the Practitioner exam is as follows:* 150 minute exam duration* 68 questions* Open book (official PRINCE2 manual only)* 38/68 required to pass = 55% pass mark [-]

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. [-]

I samarbeid med Norges bygg- og eiendomsforening og Fabrica Kulturminnetjenester AS.   Kulturminner er verdier for både publikum og eiere, men de kan også være utfordrende å utvikle på en god måte. I dette kurset vil vi formidle hva som skal til for å sikre prosesser som utløser merverdiene. Vi skal gi en innføring i begreper, regler og verdier, samt konsekvenser av fredning og annet formelt vern. Det blir en filmbefaring til Tollboden, Tolldirektoratets hovedkontor i Kvadraturen i Oslo. De har fungert som Tollsted siden 1800-tallet og har vært i bruk helt frem til 2016. Steinpakkhuset er fra 1850, mens Administrasjonsbygningen sto ferdig i 1896. [-]

Målet med kurset er å gi deltagere en oppfriskning av kunnskaper med vekt på HMS og skadereduksjon. Forkunnskap kreves, dokumentert gjennomført truckførerkurs T1 - T8. Kurset gjennomføres enten i klasserom eller webinar og tilpasses etter lokale forhold. [-]

Påmelding For påmelding til kurs se vår kursportal - IKM Testing AS - Kurs & kompetansesenter KursbeskrivelseKurset er et verktøykurs det det er fokus på å lære å benytte klammer for å utføre hot bolting på en trygg og sikker måte. Kurset består av en liten teori del, resten er praksis. På kurs skal du gjennomføre følgende: 10 godkjente gjennomføringer Minst 4 forskjellige klammer dimensjoner *Bestått kurs fornyer sertifikatet med 5 år. Ved passert 5 år uten fornyelse, eller er det opphold i arbeidet med Hot Bolting på lenger enn 6 måneder er kursbeviset ugyldig. Målgruppe & ForhåndskunnskaperKurset er for deltakere som har sertifikat for flensearbeid NS EN 1591-4.  Deltaker vil bli bedt om å fremlegge gyldig kursbevis i flensearbeid. Minimum 2 års erfaring med Flensearbeid og gode mekaniske egenskaper. Kursmateriell inkludert i pris Kompendium/oppsummering av kurs Lunsj Kaffe/te/mineralvann AvbestillingAvbestilling sendes til kurs.ikmtesting@ikm.no.Ved avbestilling senere en syv dager før kursstart, belastes kunde/deltaker full pris.Hvem som er deltaker på påmeldt kurs kan endres inn til en dag før kursstart uten at kursavgiften økes. Ved frafall på grunn av sykdom må gyldig legeerklæring fremvises for at kursavgiften skal bortfalle. IKM Testing AS tar forbehold om avlysning av kurs ved sykdom hos instruktør, for få deltakere eller force majeure. OvernattingVåre deltakere kan benytte seg av IKM Gruppen sin avtale med Smarthotel Forus forutsatt at: Bestilling av rom skjer direkte med hotellet via e-mail/telefon Bekreftelse for påmelding må vises ved innsjekk Den enkelte deltaker betaler selv for sitt opphold SpørsmålFor tekniske spørsmål eller behov for kurstilbud utover våre standard kurs vennligst ta kontakt med oss på kurs.ikmtesting@ikm.no.Vi hjelper gjerne! [-]

UTDRAG AV KURSINNHOLD: FORBEREDELSER • Rollen som rekrutterer og betydningen av gjennomføring av profesjonelle prosesser• Hvorfor vi velger feil (psykologi og feilkilder)• Hvordan forbedre prosessen (strukturet kompetansebasert rekrutteringsmetodikk)• Utarbeidelse av stillingsanalysen• Kompetansebegrepet i rekrutteringsprosessen• Bruk av kompetansekravene til å velge rekrutteringsmetode• Rekrutteringsmetodikk UTVELGELSESPROSESSEN • Feilkilder og fallgruver i utvelgelsesprosessen• Ulike utvelgelsesmetoders egnethet (validitet og reliabilitet)• Bruk av kompetansekravene fra stillingsanalysen i utvelgelsesprosessen• Vurdering og kategorisering av søknader• Riktig og feil bruk av magefølelse/intuisjon i utvelgelsen• Bruk av bakgrunnssjekk INTRODUKSJON TIL BRUK AV TESTVERKTØY • Valg av testverktøy• Feilkilder ved bruk av tester• Betydning av validitet, reliabilitet, korrelasjon og normgrupper• Evnetester• Personlighetstester, BIG5/FFM INTERVJUET • Intervjutyper• Intervjuteknikk• Forberedelse til intervjuet• Gjennomføring av intervju• Dårlige spørsmålstyper i intervjuet• Gode spørsmålstyper i intervjuet• Oppbygging av spørsmålssekvens• Intervjueradferd• Uformelle intervju• Førstegangsintervju• Dybdeintervju• Strukturert kompetansebasert intervju• Kompetansebasert vurdering av kandidaten • Forberedelse og gjennomføring av referanseintervjuet KANDIDATSAMMENLIGNING OG UTVELGELSE • Vurdering og bruk av kompetanser i kandidatvurderingen• Sammenligning av kandidaters kompetanse• Betydning av kompetansegap• Valg av kandidat MÅLGRUPPE HR-medarbeidere som ønsker å bygge opp kompetanse innenfor rekruttering og utvelgelse Ledere som selv ønsker å gjennomføre gode utvelgelsesprosesser,  For deg som vurderer en karriere innenfor fagområdet rekruttering & utvelgelse. BEGERNSET ANTALL DELTAKEREDet er begrenset antall deltakere på hvert av disse kursene. Dette er for å sikre en optimal dialog og individuell tilpasning til den enkelte deltakers behov og situasjon gjennom kurset. METODEKurset gjennomføres med en kombinasjon av teori, forelesning, og individuelle oppgaver. Praktisk gjennomføring av en utvelgelsesprosess står i fokus. Vi gir deg verktøy, hjelpemidler og maler som du kan bruke med en gang i prosessen. KURSLEDEREAlle våre kursledere har lang og bred operativ erfaring fra ledende stillinger i næringslivet. Dette kurset ledes av en erfaren bedriftsrådgiver som arbeider med rekruttering, search og utvelgelse til daglig Ta kontakt hvis du ønsker tilbud på bedriftsinternt kurs. PRAKTISKE OPPLYSNINGERKurset gjennomføres i Raad Gruppens kurslokaler og går over 1 dag fra kl. 08.30-16.00. Kurset kan også gjennomføres som et bedriftsinternt kurs eller workshop. [-]

Målsetting Målsetningen med opplæringen er å gi grunnleggende kunnskaper som kreves av en arbeidsgiver og arbeidstakere for at de skal kunne utføre varme arbeider på en sikker og forsvarlig måte, sveising, loddearbeid, vinkelsliper osv. Emneliste Innledning Sertifiseringsordningen Lover og forskrifter Forsikringsforhold Brannteori Brannslokning Verneutstyr og førstehjelp Risikovurdering Forebyggende tiltak i forbindelse med arbeidet Kontroll og rydding etter arbeid Rutiner ved brann Evaluering Avslutningsprøve Teoriprøve min. 20 spørsmål, min. 80% riktig besvarelse for å få bestått Kompetansebevis / sertifikat Et kursbevis vil bli utstedt til hver kandidat som har gjennomført og bestått opplæringen.Kursbeviset vil inneholde informasjon om opplæringssted, kursinnhold, dato for gjennomføring, kandidatens navn og fødselsdato og være signert av daglig leder/kurs koordinator [-]

Vil du lære å lage visittkort, annonser, brosjyrer og plakater i InDesign? Enten du jobber i en markedsavdeling, grafisk bedrift, avis eller magasin, er dette det profesjonelle programmet du bruker til jobben.  Arbeider du med markedsføring og layout, vil du ha stor nytte av å kunne sette sammen tekst og bilder selv. Du slipper å sette ut arbeidet,  får større kontroll på layouten og mer ut av markedsbudsjettet. Du velger dette kurset for å lære alt du trenger for å komme igang med programmet InDesign. Hvem passer kurset for? Kurset passer for deg som har liten eller ingen erfaring med å jobbe i InDesign. InDesign er bransjestandarden for å lage annonser, brosjyrer, magasiner, plakater, DM, rapporter og bøker. Uansett hva du skal bruke programme til, så passer dette kurset for deg! Dette lærer du: Bli kjent med menyer og verktøy Effektiv jobbing med tekst- og sidemaler Grunnleggende typografi Importere og tilpasse bilder og tekst Plassere bilder med tekst rundt Lage egne farger Bruk av effekter Kontroll av dokumenter og eksport til pdf https://igm.no/indesign-grunnkurs/ [-]