Oversikt over relevante kurs innen IT-kurs i Nordland

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 - 40 spørsmål skal besvares, og du består med 70% riktige svar (dvs. 28 av 40). Deltakerne har 1 time og 30 minutter til rådighet på eksamen.  Ingen hjelpemidler er tillatt.  Nødvendige forkunnskaper: Bestått ITIL Foundation sertifisering Gjennomført godkjent kurs/e-læring [-]

COURSE OVERVIEW  This course covers the process of designing, implementing, and managing core Azure networking infrastructure, Hybrid Networking connections, load balancing traffic, network routing, private access to Azure services, network security and monitoring. Learn how to design and implement a secure, reliable, network infrastructure in Azure and how to establish hybrid connectivity, routing, private access to Azure services, and monitoring in Azure. TARGET AUDIENCE This course is aimed at Network Engineers looking to specialize in Azure networking solutions. An Azure Network engineer designs and implements core Azure networking infrastructure, hybrid networking connections, load balance traffic, network routing, private access to Azure services, network security and monitoring. The azure network engineer will manage networking solutions for optimal performance, resiliency, scale, and security. COURSE CONTENT Module 1: Azure Virtual Networks In this module you will learn how to design and implement fundamental Azure Networking resources such as virtual networks, public and private IPs, DNS, virtual network peering, routing, and Azure Virtual NAT. Azure Virtual Networks Public IP Services Public and Private DNS Cross-VNet connectivity Virtual Network Routing Azure virtual Network NAT Lab 1: Design and implement a Virtual Network in Azure Lab 2: Configure DNS settings in Azure Lab 3: Connect Virtual Networks with Peering After completing module 1, students will be able to: Implement virtual networks Configure public IP services Configure private and public DNS zones Design and implement cross-VNET connectivity Implement virtual network routing Design and implement an Azure Virtual Network NAT   Module 2: Design and Implement Hybrid Networking In this module you will learn how to design and implement hybrid networking solutions such as Site-to-Site VPN connections, Point-to-Site VPN connections, Azure Virtual WAN and Virtual WAN hubs. Site-to-site VPN connection Point-to-Site VP connections Azure Virtual WAN Lab 4: Create and configure a local gateway Create and configure a virtual network gateway Create a Virtual WAN by using Azure Portal Design and implement a site-to-site VPN connection Design and implement a point-to-site VPN connection Design and implement authentication Design and implement Azure Virtual WAN Resources   Module 3: Design and implement Azure ExpressRoute In this module you will learn how to design and implement Azure ExpressRoute, ExpressRoute Global Reach, ExpressRoute FastPath and ExpressRoute Peering options. ExpressRoute ExpressRoute Direct ExpressRoute FastPath ExpressRoute Peering Lab 5: Create and configure ExpressRoute Design and implement Expressroute Design and implement Expressroute Direct Design and implement Expressroute FastPath   Module 4: load balancing non-HTTP(S) traffic in Azure In this module you will learn how to design and implement load balancing solutions for non-HTTP(S) traffic in Azure with Azure Load balancer and Traffic Manager. Content Delivery and Load Blancing Azure Load balancer Azure Traffic Manager Azure Monitor Network Watcher Lab 6: Create and configure a public load balancer to load balance VMs using the Azure portal Lab:7 Create a Traffic Manager Profile using the Azure portal Lab 8: Create, view, and manage metric alerts in Azure Monitor Design and implement Azure Laod Balancers Design and implement Azure Traffic Manager Monitor Networks with Azure Monitor Use Network Watcher   Module 5: Load balancing HTTP(S) traffic in Azure In this module you will learn how to design and implement load balancing solutions for HTTP(S) traffic in Azure with Azure Application gateway and Azure Front Door. Azure Application Gateway Azure Front Door Lab 9: Create a Front Door for a highly available web application using the Azure portal Lab 10: Create and Configure an Application Gateway Design and implement Azure Application Gateway Implement Azure Front Door   Module 6: Design and implement network security In this module you will learn to design and imponent network security solutions such as Azure DDoS, Azure Firewalls, Network Security Groups, and Web Application Firewall. Azure DDoS Protection Azure Firewall Network Security Groups Web Application Firewall on Azure Front Door Lab 11: Create a Virtual Network with DDoS protection plan Lab 12: Deploy and Configure Azure Firewall Lab 13: Create a Web Application Firewall policy on Azure Front Door Configure and monitor an Azure DDoS protection plan implement and manage Azure Firewall Implement network security groups Implement a web application firewall (WAF) on Azure Front Door   Module 7: Design and implement private access to Azure Services In this module you will learn to design and implement private access to Azure Services with Azure Private Link, and virtual network service endpoints. Define Azure Private Link and private endpoints Design and Configure Private Endpoints Integrate a Private Link with DNS and on-premises clients Create, configure, and provide access to Service Endpoints Configure VNET integration for App Service Lab 14: restrict network access to PaaS resources with virtual network service endpoints Lab 15: create an Azure private endpoint Define the difference between Private Link Service and private endpoints Design and configure private endpoints Explain virtual network service endpoints Design and configure access to service endpoints Integrate Private Link with DNS Integrate your App Service with Azure virtual networks   TEST CERTIFICATION This course helps to prepare for exam AZ-700 [-]

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. [-]

Dette kurset tilbys som bedriftsinternt kurs   Kursinstruktør Lloyd Roden Loyd har over 30 års er faring fra IT-bransjen. Han har jobbet som utvikler, ledet en uavhengig test gruppe innenfor et programvarehus og har jobbet 10 år i  UK-baserte Grove Consultants som konsulent/partner. I 2011 startet han eget konsulentselskap med software testing som spesialfelt. Lloyd har holdt foredrag på konferanser som STAREAST, STARWEST, Eurostar, AsiaSTAR, Software Test Automation, Test Kongressen, og Unicom m.fl.   Lloyd Rodens verdier:"Jeg ønsker at arbeidet som jeg gjør, enten det er i form av rådgivning eller opplæring, må være relevant, praktisk og må gjøre en forskjell for den enkelte samt organisasjonen. Det er viktig for meg at deltakerne på mine kurs forbedrer sine ferdigheter i softwaretesting, og at dette til slutt vil gjenspeile seg i den forbedrede kvaliteten på produktene som leveres av organisasjonen."   Kursinnhold This 1-day workshop is aimed at Test Leaders and Test Managers wanting to improve their test reporting skills. Gathering and presenting clear information about quality, both product and process, may be the most important part of the test managerÍs job. Test reports need to be concise, predictive, accurate and relevant to the people receiving them. This workshop demonstrates 9 powerful monitoring techniques and shows how the test manager's dashboard can be tailored to the recipient's needs. Monitoring utilities will be demonstrated and provided during the workshop.   [-]

Excel controllere/økonomer kurs vinklet fra en Controllers hverdag med fokus på gode metoder for å arbeide med Excel-lister. Påfyllet kurset gir deg, gjør deg i stand til å jobbe mer effektivt i Excel. Kursets mange eksempler, viser hva du virkelig kan få til i Excel, enten det er å jobbe med formler / funksjoner, lister eller store Excel-modeller. Kurset er utviklet av controllere, med det for øye at du skal kunne angripe dine Excel-utfordringer på en smart og effektiv måte. Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:     Datautveksling/Klargjøring av data Mulige inndatametoder: Importering av tekstfil, webspørringer, innliming av data fra WWW. Importere data med ulikt dataformat: tekst - eller databaseformat Formatproblemer ifm. dataimport: ”feil” formater, fjerne deler av informasjon i en celle, fjerne duplikater, kjapt finne skrivefeil   Data/Konsolider Konsolider data: hvor data ligger i samme regneark Konsolidering data: hvor dataene skal behandles på tvers av regneark. Konsolidering data: hvor data ligger i ulike arbeidsbøker   Tabeller/Listefunksjonalitet Definisjonen av en tabell: Viktig å huske når tabellen skal behandles videre. Jobbe med en liste: få gode råd angående arbeid med lister Sortere tabellen: kjapt og enkelt med egendefinerte sorteringsnøkler Filter med Autofilter: filtrere ut bare de data du ønsker eller slette tomme rader. Filter med Avansert filter: få råd om i hvilke situasjoner det er smart å bruke avansert filter og hvordan du enklest bruker dette filteret. Beregninger i tabeller og lister Beregninger med flere variabler: Funksjonene Dsummer, Dantall og DGjennomsnitt Organiser og beregne data : Ved hjelp av delsammendrag. Lær hvordan resultatet kan kopieres til et annet sted. Oppslag i en liste: Funksjonene Finn.Kolonne og Finn.Rad Lag rapporter ved hjelp av Pivotteknikk: Opplev hvor enkelt det er å lage rapporter ved hjelp av pivotteknikk!   "Hva hvis"-analyser og optimalisering Sensitivitetsanalyse: Målsøking er en måte å regne ”baklengs” på. Sensitivitetsanalyse: Tabeller med 1 og 2 variabler Optimalisering: Ved hjelp av Problemløseren   Samarbeid med andre Deling av arbeidsbøker: ved ønske om å jobbe samtidig i samme arbeidsbok Sporing av endringer: når du ønsker å plukke opp de endringer andre har gjort     4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms TARGET AUDIENCE Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. COURSE OBJECTIVES Plan for the transformation with shared goals and timelines Select a project and identify project metrics and Key Performance Indicators (KPI's) Create a team and agile organizational structure Design a tool integration strategy Design a license management strategy (e.g., Azure DevOps and GitHub users) Design a strategy for end-to-end traceability from work items to working software Design an authentication and access strategy Design a strategy for integrating on-premises and cloud resources Describe the benefits of using Source Control Describe Azure Repos and GitHub Migrate from TFVC to Git Manage code quality, including technical debt SonarCloud, and other tooling solutions Build organizational knowledge on code quality Explain how to structure Git repos Describe Git branching workflows Leverage pull requests for collaboration and code reviews Leverage Git hooks for automation Use Git to foster inner source across the organization Explain the role of Azure Pipelines and its components Configure Agents for use in Azure Pipelines Explain why continuous integration matters Implement continuous integration using Azure Pipelines Design processes to measure end-user satisfaction and analyze user feedback Design processes to automate application analytics Manage alerts and reduce meaningless and non-actionable alerts Carry out blameless retrospectives and create a just culture Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure Implement compliance and security in your application infrastructure Describe the potential challenges with integrating open-source software Inspect open-source software packages for security and license compliance Manage organizational security and compliance policies Integrate license and vulnerability scans into build and deployment pipelines Configure build pipelines to access package security and license ratings   COURSE CONTENT Module 1: Get started on a DevOps transformation journey Module 1 Lessons Introduction to DevOps Choose the right project Describe team structures Choose the DevOps tools Plan Agile with GitHub Projects and Azure Boards Introduction to source control Describe types of source control systems Work with Azure Repos and GitHub Lab 1: Agile planning and portfolio management with Azure Boards   Lab 2: Version controlling with Git in Azure Repos   After completing Module 1, students will be able to: Understand what DevOps is and the steps to accomplish it Identify teams to implement the process Plan for the transformation with shared goals and timelines Plan and define timelines for goals Understand different projects and systems to guide the journey Select a project to start the DevOps transformation Identify groups to minimize initial resistance Identify project metrics and Key Performance Indicators (KPI's) Understand agile practices and principles of agile development Create a team and agile organizational structure Module 2: Development for enterprise DevOps Module 2 Lessons Structure your Git Repo Manage Git branches and workflows Collaborate with pull requests in Azure Repos Explore Git hooks Plan foster inner source Manage Git repositories Identify technical debt Lab 3: Version controlling with Git in Azure Repos   After completing Module 2, students will be able to: Understand Git repositories Implement mono repo or multiple repos Explain how to structure Git Repos Implement a change log Describe Git branching workflows Implement feature branches Implement GitFlow Fork a repo Leverage pull requests for collaboration and code reviews Give feedback using pull requests Module 3: Implement CI with Azure Pipelines and GitHub Actions Module 3 Lessons Explore Azure Pipelines Manage Azure Pipeline agents and pools Describe pipelines and concurrency Explore Continuous integration Implement a pipeline strategy Integrate with Azure Pipelines Introduction to GitHub Actions Learn continuous integration with GitHub Actions Design a container build strategy Lab 4: Configuring agent pools and understanding pipeline styles   Lab 5: Enabling continuous integration with Azure Pipelines   Lab 6: Integrating external source control with Azure Pipelines   Lab 7: Implementing GitHub Actions by using DevOps Starter   Lab 8: Deploying Docker Containers to Azure App Service web apps   After completing Module 3, students will be able to: Describe Azure Pipelines Explain the role of Azure Pipelines and its components Decide Pipeline automation responsibility Understand Azure Pipeline key terms Choose between Microsoft-hosted and self-hosted agents Install and configure Azure pipelines Agents Configure agent pools Make the agents and pools secure Use and estimate parallel jobs Module 4: Design and implement a release strategy Module 4 Lessons Introduction to continuous delivery Create a release pipeline Explore release strategy recommendations Provision and test environments Manage and modularize tasks and templates Automate inspection of health Lab 9: Creating a release dashboard   Lab 10: Controlling deployments using Release Gates   After completing Module 4, students will be able to: Explain continuous delivery (CD) Implement continuous delivery in your development cycle Understand releases and deployment Identify project opportunities to apply CD Explain things to consider when designing your release strategy Define the components of a release pipeline and use artifact sources Create a release approval plan Implement release gates Differentiate between a release and a deployment Module 5: Implement a secure continuous deployment using Azure Pipelines Module 5 Lessons Introduction to deployment patterns Implement blue-green deployment and feature toggles Implement canary releases and dark launching Implement A/B testing and progressive exposure deployment Integrate with identity management systems Manage application configuration data Lab 11: Configuring pipelines as code with YAML   Lab 12: Setting up and running functional tests   Lab 13: Integrating Azure Key Vault with Azure DevOps   After completing Module 5, students will be able to: Explain the terminology used in Azure DevOps and other Release Management Tooling Describe what a Build and Release task is, what it can do, and some available deployment tasks Implement release jobs Differentiate between multi-agent and multi-configuration release job Provision and configure target environment Deploy to an environment securely using a service connection Configure functional test automation and run availability tests Setup test infrastructure Use and manage task and variable groups Module 6: Manage infrastructure as code using Azure and DSC Module 6 Lessons Explore infrastructure as code and configuration management Create Azure resources using Azure Resource Manager templates Create Azure resources by using Azure CLI Explore Azure Automation with DevOps Implement Desired State Configuration (DSC) Implement Bicep Lab 14: Azure deployments using Azure Resource Manager templates   After completing Module 6, students will be able to: Understand how to deploy your environment Plan your environment configuration Choose between imperative versus declarative configuration Explain idempotent configuration Create Azure resources using ARM templates Understand ARM templates and template components Manage dependencies and secrets in templates Organize and modularize templates Create Azure resources using Azure CLI Module 7: Implement security and validate code bases for compliance Module 7 Lessons Introduction to Secure DevOps Implement open-source software Software Composition Analysis Static analyzers OWASP and Dynamic Analyzers Security Monitoring and Governance Lab 15: Implement security and compliance in Azure Pipelines   Lab 16: Managing technical debt with SonarQube and Azure DevOps   After completing Module 7, students will be able to: Identify SQL injection attack Understand DevSecOps Implement pipeline security Understand threat modeling Implement open-source software Explain corporate concerns for open-source components Describe open-source licenses Understand the license implications and ratings Work with Static and Dynamic Analyzers Configure Microsoft Defender for Cloud Module 8: Design and implement a dependency management strategy Module 8 Lessons Explore package dependencies Understand package management Migrate, consolidate, and secure artifacts Implement a versioning strategy Introduction to GitHub Packages Lab 17: Package management with Azure Artifacts   After completing Module 8, students will be able to: Define dependency management strategy Identify dependencies Describe elements and componentization of a dependency management Scan your codebase for dependencies Implement package management Manage package feed Consume and create packages Publish packages Identify artifact repositories Migrate and integrate artifact repositories Module 9: Implement continuous feedback Module 9 Lessons Implement tools to track usage and flow Develop monitor and status dashboards Share knowledge within teams Design processes to automate application analytics Manage alerts, Blameless retrospectives and a just culture Lab 18: Monitoring application performance with Application Insights   Lab 19: Integration between Azure DevOps and Microsoft Teams   Lab 20: Sharing Team Knowledge using Azure Project Wikis   After completing Module 9, students will be able to: Implement tools to track feedback Plan for continuous monitoring Implement Application Insights Use Kusto Query Language (KQL) Implement routing for mobile applications Configure App Center Diagnostics Configure alerts Create a bug tracker Configure Azure Dashboards Work with View Designer in Azure Monitor [-]

Kurset er rettet mot deg som skal armere i Autodesk Revit. Dette er et praktisk kurs som gjør deg i stand til å armere betongkonstruksjoner, lage armeringstegninger og bøyelister. Hensikten med kurset er å gjøre deg i stand til bruke armerinsgverktøyene i Revit samt lage armeringstegninger og bøyelister ved hjelp av verktøyene som ligger i Revit-applikasjonen Focus RAT Bygg. Du vil lære hvordan manuelt armere betongkonstruksjoner. Du vil også lære verktøyene for å lage løpemeterarmering, armeringsnett og kantarmering. Du vil lære å bruke Revit Extensions for å armere konstruksjoner automatisk. Vi skal også lage armeringstegninger og bøyelister i henhold til NS 3766. Kursinnhold: Manuell armering av betongkonstruksjoner Løpemeterarmering Kantarmering Armeringsnett Automatisk armering av betongkonstruksjoner med Revit Extensions Armere avanserte betongkonstruksjoner Lage armeringstegninger Lage bøyelister [-]

CCNA: Implementing and Administering Cisco Solutions [-]

På webinaret går vi gjennom oppsett og presentasjonsopplevelser i Microsoft Teams møter. Teams er i rask utvikling og spesielt på presentasjonsfronten har det skjedd store endringer i det siste. Dette webinaret tar for seg alternativer i oppsett av møtet, tildele riktige roller og skape den beste presentasjonsopplevelsen for deltakerne. Opprette Teams-møter – via Outlook eller Teams | Ad Hoc møter | Kanalmøter | Innstillinger for møtet – i innkallelsen | Innstillinger og administrasjon av møtet – når møtet er i gang i Teams | Visninger | Presentere/dele – hva og hvordan| Presentasjonsvisninger | Teksting | Opptak | Møtenotater – før, under og etter Pris: 1690 kroner [-]

UTDANNINGSMÅLDu vil lære grunnleggende teknikk for bruk av programmet, og skal kunne bruke programmet til å lage 3D-modeller av terreng, veier, VA. Hente ut informasjon fra modellen og kunne produsere 2D-arbeidstegninger basert på 3D-modellen. KURSINNHOLD: Norsk kursdokumentasjon Introduksjon av Civil 3D Brukergrensesnitt Behandling av visninger Etabler og arbeide med en terrengmodell Masseberegning Punktgrupper Planering av områder med tilhørende skråningsutslag Grunnleggende vegprosjektering, konstruksjon av senterlinje, lengdeprofil, tverrprofil og vegmodell med skjæring og fylling mot terreng Bearbeide terreng ved hjelp av data fra vegmodellen Grunnleggende bruk av VA funksjonaliteten med opptegning i plan og profil, og presentasjon av data Landmåling; import av feltbokfiler fra målestasjon, og produksjon av punktgrupper og terrengmodeller av dataene Tekst/Tittelfelt Detaljering Utskrift [-]

IP1: Generell nettverksteknologi [-]

MS-100: Microsoft 365 Identity and Services [-]

I kurset finner du en rekke videoklipp som viser i programmet hvordan man utfører de ulike oppgavene og presenterer resultatet av dette. Du får innsendingsoppgaver underveis som vil bli fulgt opp av en faglærer, og du har tilgang til faglærer i hele kursperioden. Du kan du stille spørsmål, både til faglærer, men også i et forum som er tilgjengelig for deltakere i kurset.Du får tilgang til vår e-læringsportal som vil gi deg god oversikt over progresjonen i kurset i et brukervennlig og enkelt system.I kurset ser vi blant annet på følgende temaer:Funksjoner: ANTALL og ANTALLA HVIS-funksjonen FINN.RAD og FINN.KOLONNE ANTALL.HVIS og SUMMERHVIS AVRUND Formatering: Dato- og tidfunksjoner Tekstfunksjoner Formatering av datoer Betinget formatering Kopiering av formatering Avansert tallformatering Beskyttelse av celler Formler og navngivning: Låsing av celler Navngivning av celler Målsøking og scenariobehandling Jobbe med lister og database: Sortering og filtrering Fjerne duplikater Pivottabeller: Datagrunnlaget og datakilder Oppsett av felt Delsummer og totalsummer Gruppere på dato Velge beregning i verdifelt Vis verdier som Formatere tall Formatere tabell Diagrammer Kurset består av tekst, bilder og en rekke videoklipp i leksjonene i kurset. Det er ikke behov for noe ytterligere dokumentasjon. Du får tilbakemeldinger fra faglærer på innsendingsoppgaver og du har tilgang til hjelp i hele kursperioden (ett år). Mer informasjon om kurset her. [-]

  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 [-]

Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring. Objectives This course teaches participants the following skills: Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform Understand how pod networking works in Kubernetes Engine Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/kubectl commands Launch, roll back and expose jobs in Kubernetes Manage access control using Kubernetes RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine   Course Outline Module 1: Introduction to Google Cloud Platform Use the Google Cloud Platform Console Use Cloud Shell Define cloud computing Identify GCP’s compute services Understand regions and zones Understand the cloud resource hierarchy Administer your GCP resources Module 2: Containers and Kubernetes in GCP 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 GCP compute platforms Module 3: Kubernetes Architecture Understand the architecture of Kubernetes: pods, namespaces Understand the control-plane components of Kubernetes Create container images using Google Cloud Build Store container images in Google Container Registry Create a Kubernetes Engine cluster Module 4: Kubernetes Operations Work with the kubectl command Inspect the cluster and Pods View a Pod’s console output Sign in to a Pod interactivelty Module 5: Deployment, Jobs, and Scaling Create and use Deployments Create and run Jobs and CronJobs Scale clusters manually and automatically Configure Node and Pod affinity Get software into your cluster with Helm charts and Kubernetes Marketplace Module 6: GKE Networking Create Services to expose applications that are running within Pods Use load balancers to expose Services to external clients Create Ingress resources for HTTP(S) load balancing Leverage container-native load balancing to improve Pod load balancing Define Kubernetes network policies to allow and block traffic to pods Module 7: Persistent Data and Storage Use Secrets to isolate security credentials Use ConfigMaps to isolate configuration artifacts Push out and roll back updates to Secrets and ConfigMaps Configure Persistent Storage Volumes for Kubernetes Pods Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts Module 8: Access Control and Security in Kubernetes and Kubernetes Engine Understand Kubernetes authentication and authorization Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources Define Kubernetes pod security policies Understand the structure of GCP IAM Define IAM roles and policies for Kubernetes Engine cluster administration Module 9: Logging and Monitoring Use Stackdriver to monitor and manage availability and performance Locate and inspect Kubernetes logs Create probes for wellness checks on live applications Module 10: Using GCP Managed Storage Services from Kubernetes Applications Understand pros and cons for using a managed storage service versus self-managed containerized storage Enable applications running in GKE to access GCP storage services Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and BigQuery from within a Kubernetes application [-]