Oversikt over relevante kurs innen IT-kurs i Vestvågøy

Understand the purpose and key concepts of Information Security Management, elucidating its significance in safeguarding the confidentiality, integrity, and availability of organisational information assets. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

Dette nettkurset fokuserer på objektorientert programmering (OOP) i Python og er ideelt for de som allerede har grunnleggende ferdigheter i Python og ønsker å utvide sine kunnskaper. OOP gir deg muligheten til å skrive kode som er mer strukturert, gjenbrukbar og enklere å vedlikeholde. Kurset, ledet av erfaren systemutvikler og instruktør Magnus Kvendseth Øye, vil veilede deg gjennom nøkkelkonsepter innen OOP i Python. I løpet av kurset vil du lære å se på koden din som en samling av dynamiske objekter som samhandler med hverandre. Du vil utforske følgende emner: Kapittel 1: Introduksjon Kapittel 2: Klasser og egenskaper Kapittel 3: Metoder Kapittel 4: Representasjon Kapittel 5: Arv Kapittel 6: Prosjekt Kapittel 7: Avslutning Med Magnus Kvendseth Øye som din veileder, vil du få en solid forståelse av hvordan du kan bruke OOP-prinsipper i Python for å skape ren, effektiv og strukturert kode. Dette kurset gir deg muligheten til å ta dine Python-ferdigheter til neste nivå.   Varighet: 3 timer og 8 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Vår tjeneste fungerer på samme måte som strømmetjenester for musikk eller TV-serier, der våre kunder betaler en fast månedspris for tilgang til alle kursene vi har tilgjengelig. Vi har opplevd betydelig vekst de siste årene, med over 30 000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling engasjerende, spennende og tilgjengelig for alle, og vi har støtte fra Innovasjon Norge og Forskningsrådet. [-]

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. [-]

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

The course will cover general cloud computing concepts as well as general cloud computing models and services such as Public, Private and Hybrid cloud and Infrastructure-as-a-Service (IaaS), Platform-as-a-Service(PaaS) and Software-as-a-Service (SaaS). It will also cover some core Azure services and solutions, as well as key Azure pillar services concerning security, privacy, compliance and trust. It will finally cover pricing and support services available.   Agenda Module 1: Cloud Concepts -Learning Objectives-Why Cloud Services?-Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS)-Public, Private, and Hybrid cloud models Module 2: Core Azure Services -Core Azure architectural components-Core Azure Services and Products-Azure Solutions-Azure management tools Module 3: Security, Privacy, Compliance and Trust -Securing network connectivity in Azure-Core Azure Identity services-Security tools and features-Azure governance methodologies-Monitoring and Reporting in Azure-Privacy, Compliance and Data Protection standards in Azure Module 4: Azure Pricing and Support -Azure subscriptions-Planning and managing costs-Support options available with Azure-Service lifecycle in Azure [-]

Datagrunnlaget Gruppering Formatering Tallformater Visningsalternativer Feltinnstillinger Beregnede felt Bruk av flere pivottabeller i samme arbeidsbok Slicere som virker på flere pivottabeller eller pivotdiagrammer Tabellfunksjonalitet   Analyse av pivotdiagram Bruk av pivotdiagram i andre programmer   et er fordelaktig å ha to skjermer - en til å følge kurset og en til å gjøre det kursholder demonstrerer. Kurset gjennomføres i sanntid med nettundervisning via Teams. Det blir mulighet for å stille spørsmål, ha diskusjoner, demonstrasjoner og øvelser. Du vil motta en invitasjon til Teams fra kursholder.   [-]

Kurset inneholder 12 timer med undervisning, er delt inn i moduler og er en blanding av video og interaktive øvelse. Du vil få en omfattende introduksjon til kjernekonseptene til ITIL® 4.   Les mer om ITIL® 4 på AXELOS sine websider    The ITIL®  4 Foundation Online course on this page is offered by ILX Group an ATO of AXELOS Limited. ITIL® 4 is a registered trade mark of AXELOS Limited, used under permission of AXELOS Limited. All rights reserved.   Dette inngår i kurset - 12 måneders tilgang til kurset fra kjøpsdato- Support service- En testmodul med spørsmål rettet mot sertifiseringseksamen Sertifiseringseksamen - Eksamens voucher er inklusive i kurset- Det er ingen hjelpemidler tillatt under eksamen- Varighet er 60 minutter, men et tillegg på 15 minutter for de som ikke har engelsk som morsmål- Eksamensformen er multiple choice - 40 spørsmål skal besvares, og du består ved 65% korrekte svar (dvs 26 av 40 spørsmål) Disse modulene inngår i kurset - Introduction and overview- Key concepts of service management- Four dimensions of service management- Service value system- Introduction to practices- Purpose of 11 practices and some definitions- Introduction to seven key practices in detail- Continual improvement- Change control- Incident management- Service request management- Service desk- Service level management- Exam simulator Etter endt kurs vil du - Forstå nøkkelkonseptene for ITIL-Service Management- Forstå hvordan ITIL-veiledende prinsipper kan hjelpe organisasjoner til å ta i bruk og tilpasse ITIL-Service Management- Forstå de fire dimensjonene i ITIL-Service Management- Forstå nøkkelbegrepene for kontinuerlig forbedring [-]

Objectives Describe specialized data classifications on Azure Identify Azure data protection mechanisms Implement Azure data encryption methods Secure Internet protocols and how to implement them on Azure Describe Azure security services and features Agenda Module 1: Identity and Access -Configure Azure Active Directory for Azure workloads and subscriptions-Configure Azure AD Privileged Identity Management-Configure security for an Azure subscription Module 2: Platform Protection -Understand cloud security-Build a network-Secure network-Implement host security-Implement platform security-Implement subscription security Module 3: Security Operations -Configure security services-Configure security policies by using Azure Security Center-Manage security alerts-Respond to and remediate security issues-Create security baselines Module 4: Data and applications -Configure security policies to manage data-Configure security for data infrastructure-Configure encryption for data at rest-Understand application security-Implement security for application lifecycle-Secure applications-Configure and manage Azure Key Vault       [-]

SFWIPA: Securing Data Center Networks and VPNs with Cisco Secure Firewall Threat Defense [-]

Dette kurset tilbys som bedriftsinternt kurs   Maskinlæring handler om sette datamaskiner i stand til å lære fra og utvikle atferd basert på data. Det vil si at en datamaskin kan løse en oppgave den ikke er eksplisitt programmert for å håndtere. I stedet er den i stand til å automatisk lære gjenkjenning av komplekse mønstre i data og gjøre beslutninger basert på dette disse. Maskinlæring gir store muligheter, men mange bedrifter har problemer med å ta teknologien i bruk. Nøyaktig hvilke oppgaver kan maskinlæring utføre, og hvordan kommer man i gang? Dette kurset gir oversikt over mulighetene som ligger i maskinlæring, og hvordan i tillegg til kunnskap om hvordan teknologien kan løse oppgaver og skape resultater i praksis. Hva er maskinlæring, datavitenskap og kunstig intelligens og hvordan det er relatert til statistikk og dataanalyse? Hvordan å utvinne kunnskap fra dataene dine? Hva betyr Big data og hvordan analyseres det? Hvor og hvordan skal du bruke maskinlæring til dine daglige forretningsproblemer? Hvordan bruke datamønstre til å ta avgjørelser og spådommer med eksempler fra den virkelige verden? Hvilke typer forretningsproblemer kan en maskinen lære å håndtere Muligheter som maskinlæring gir din bedrift Hva er de teoretiske aspekter på metoder innen maskinlæring? Hvilke ML-metoder som er relevante for ulike problemstillinger innen dataanalyse? Hvordan evaluere styrker og svakheter mellom disse algoritmene og velge den beste? Anvendt data science og konkrete kunde eksempler i praksis   Målsetning Kurset gir kunnskap om hvordan maskinlæring kan løse et bestemt problem og hvilke metoder som egner seg i en gitt situasjon. Du blir i stand til å kan skaffe deg innsikt i data, og vil kunne identifisere egenskapene som representerer dem best. Du kjenner de viktigste maskinlæringsalgoritmene og hvilke metoder som evaluerer ytelsen deres best. Dette gir grunnlag for kontinuerlig forbedring av løsninger basert på maskinlæring.   [-]

Blended Virtual CourseThe course is a hybrid of virtual training and self-study which will be a mixture of teaching using Microsoft Teams for short bursts at the beginning of the day, then setting work for the rest of the day and then coming back at the end of the day for another on-line session for any questions before setting homework in the form of practice exams for the evening. You do not have to install Microsoft Teams, you will receive a link and can access the course using the web browser.  Remote proctored examTake your exam from any location. Read about iSQI remote proctored exam here Requirements for the exam: The exam will be using Google Chrome and there is a plug-in that needs to be installed  You will need a laptop/PC with a camera and a microphone  A current ID with a picture    KursinnholdDette kurset forklarer det grunnleggende i softwaretesting. Det er basert på ISTQB- pensum og er akkreditert av BCS.    Kurset inneholder øvelser, prøveeksamener og spill for å fremheve sentrale deler av pensum. Dette sammen med kursmateriell og presentasjoner vil bistå i forståelse av begreper og metoder som blir presentert.   Bouvet sine kursdeltakeres testresultater vs ISTQB gjennomsnitt   «Særs godt kurs med mye fokus på praktiske oppgaver som gjør læring vesentlig lettere. Engasjert kursleder hjelper også. Kursleder starter på et nivå som alle føler seg komfortabel med.» Alexander Røstum Course content Fundamentals of Testing This section looks at why testing is necessary, what testing is, and explains general testing principles, the fundamental test process, and psychological aspects of testing.   Skills Gained • Learn about the differences between the testing levels and targets• Know how to apply both black and white box approaches to all levels of testing• Understand the differences between the various types of review and be aware of Static Analysis• Learn aspects of test planning, estimation, monitoring and control• Communicate better through understanding standard definitions of terms• Gain knowledge of the different types of testing tools and the best way of implementing those tools   Testing throughout the software lifecycle Explains the relationship between testing and life cycle development models, including the V-model and iterative development. Outlines four levels of testing:• Component testing• Integration testing• System testing• Acceptance testing Describes four test types, the targets of testing:• functional• non-functional characteristics• structural• change-related Outlines the role of testing in maintenance.   Static Techniques Explains the differences between the various types of review, and outlines the characteristics of a formal review. Describes how static analysis can find defects.   Test Design Techniques This section explains how to identify test conditions (things to test) and how to design test cases and procedures. It also explains the difference between white and black box testing. The following techniques are described in some detail with practical exercises :• Equivalence Partitioning• Boundary Value Analysis• Decision Tables• State Transition testing• Statement and Decision testingIn addition, use case testing and experience-based testing (such as exploratory testing) are described, and advice is given on choosing techniques.   Test Management This section looks at organisational implications for testing and describes test planning and estimation, test monitoring and control. The relationship of testing and risk is covered,and configuration management and incident management.   Tool Support for Testing Different types of tool support for testing are described throughout the course. This session summarises them, and discusses how to use them effectively and how best to introduce a new tool.   The Exam The ISTQB Foundation exam is a 1-hour, 40 question multiple choice exam. There is an extra 15 minutes allowed for candidates whose first language is not English.The pass mark is 65% (26/40) and there are no pre requisites to taking this exam.The exam is a remote proctored exam [-]

Her starter vi ganske på begynnelsen, og går ut fra at deltagerne har liten eller ingen erfaring med Excel. Vi starter med de grunnleggende prinsippene, og bygger så videre på dem. I stikkordsform ser innholdet ut slik: Regnearkets oppbygning – grunnprinsipper Tall og tekst – identifisere og korrigere/konvertere Listefunksjonalitet – sortere, filtrere, redigere, skrive ut, etc. Grunnleggende formelbygging – de fire regneartene Kopiering av formler – absolutte og relative referanser Sentrale funksjoner: SUMMER, GJENNOMSNITT, HVIS,   HVISFEIL Modellbyggingsteknikker - sammendrag av data over flere ark Grafiske fremstillinger av numeriske data Identifisere og fjerne duplikatverdier fra en liste Arbeide med tid (dager, klokkeslett, etc.) i Excel [-]

AI-3016: Develop custom copilots with Azure AI Studio [-]

Vue.js, Vuex & Router Course [-]

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.   Revit Architecture Basis I Her er et utvalg av temaene du vil lære på kurset: Introduksjon til BIM Modellering av 3D-bygningsmodell i flere detaljeringsgrader (informasjonsnivåer) Samarbeid med andre fagmodeller Generering av planer, snitt, fasader, detaljer og perspektiver Skjemaer og mengdeuttrekk Oppsetning til print A Anvendelse av relevante NTItools Kurset gir deg innblikk i bruken av BIM-arbeidsmetoder med Revit som hovedverktøy. Det bygges opp en full, parametrisk 3D-modell, hvor de grunnleggende funksjonene i Revit benyttes. DU vil få en bred forståelse av både prinsipper og funksjoner i Revit og skal bli i stand til å øke detaljeringen av prosjektet ytterligere.   Dette er et populært kurs, meld deg på nå!   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 [-]