Oversikt over relevante kurs innen IT-kurs i Skonseng

Ønsker du en kjapp og smertefri introduksjon i verdens mest populære bildebehandlingsprogram? Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1    Innføring Fargemodellene RGB og CMYK Beskjæring av bildet til trykk eller skjerm Utskriftsoppløsning og kameraoppløsning Forstå hvordan oppløsning fungerer Hva er de vanligste filformatene å jobbe i   Arbeidsmiljø Menyer og paletter. Hva inneholder disse, og hvordan får du fram det du ønsker? Tilpasse arbeidsmiljøet. Flytte på paletter og lagre egne oppsett tilpasset dine behov Navigering og zoom. Fokuser på det du jobber med, se helheten, og gjør dette raskt og effektivt Adobe Bridge. Introduksjon til programmet som organiserer og forhåndsviser filer og gjør det enklere for deg å jobbe Nytt dokument. Hvordan lage og tilpasse nye dokumenter med marger, spalter, sidevisning med mer?   Retusjering Bli kjent med retusjeringsverktøyene Se på hvilke muligheter du har i nyere utgave av Photoshop Fjerne uønskede elementer i bilder   Lag Bli kjent med lagpaletten Opprette, slette og organisere lag Transformering av lag Lagstiler og justeringslag   Markeringer Lær å bruke de forskjellige markeringsverktøyene Gjøre endringer på markerte områder Kombiner markeringsverktøy for å kun få tak i det du ønsker Opprett lag på bakgrunn av markeringer   Dag 2   Bildejusteringer Justere kontrast og tonalitet i et bilde Jobbe med å gjøre bilde lysere og mørkere Justere farger i et bilde Bytte ut én farge med en annen   Kombiner ulike verktøy for å utnytte mulighetene i Photoshop Jobbe med et bilde med ulike verktøy Markering og bildejustering Markering og fjerning av bakgrunnselementer Bruke smartere markedsverktøy   Lagring Lær om de ulike filformatene vi bør kjenne til Lagring til web og komprimering av bilder Lagring til trykk   Jobbe med flere bilder Klippe ut fra et bilde og lime inn i et annet Tekstverktøyet og tekstpalettene Tegneverktøy   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

Excel – Du trodde du kunne det? [-]

Excel Ekspert kurs for deg som ønsker en omfattende fordypning i Excel knyttet til formler og funksjoner, men som ikke har tid til å sette deg inn i dette på egenhånd. Vil du lære mer om håndtering av datagrunnlag og rapportering på grunnlag fra flere kilder, samt bygging av dynamiske modeller? Da er ”Excel Ekspert” kurset for deg! Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1   Funksjoner i Excel Utarbeidelse av dynamiske modeller ved bruk av navn og funksjoner. Funksjoner. Få oversikt over flere avanserte funksjoner samt se kraften av å bruke sammensatte funksjoner Navn. Bruk navn for å forenkle og tydeliggjøre formler og funksjoner. Lag dynamiske etiketter til diagrammer Matriseregning. Få en innføring i hvordan du kan jobbe med matrisefunksjonalitet i Excel.   Alternativknapper og kombinasjonsbokser Gjør modellene dine mer interaktive ved bruk av kontroller   Dag 2   Klargjøre data for beregninger ved bruk av PowerQuery Hva er PowerQuery? Lese inn data til PowerQuery fra ulike kilder Eksempel: tilføye og slå sammen Snu krysstabell Kobling til tekstfil med problemer Manglende struktur i kolonner. Lær hvordan du kan gjengi informasjon i regnearket slik at grunnlaget kan brukes til rapportering. Duplikater. Lær forskjellige måter å kvitte seg med duplikater på. Splitte informasjon. Lær forskjellige måter for å skille data i kolonner.   Beregninger ved bruk av Pivot Eksempel: prosentvis fordeling ”i år mot i fjor”. Pivotkonsolidering og datakonsolidering.   Makroer Innspilling av makro. Hvordan lage makroer for å automatisere rutinearbeid? Redigering av makroer. Lær hvordan makroer kan gjøres mer dynamiske, kombinert med navn og bruk av meldingsbokser og ”hvis” setninger. Demonstrere viktige VBA metoder 4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti     [-]

Excel for Selgere - elæringskurs [-]

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 [-]

AZ-700: Designing and Implementing Microsoft Azure Networking Solutions [-]

AZ-900: Microsoft Azure Fundamentals [-]

  An Azure IoT Developer is responsible for implementing and then maintaining the cloud and edge portions of an Azure IoT solution. In addition to configuring and maintaining devices by using Azure IoT services and other Microsoft tools, the IoT Developer also sets up the physical devices and is responsible for maintaining the devices throughout the life cycle. The IoT Developer implements designs for IoT solutions, including device topology, connectivity, debugging and security. For Edge device scenarios, the IoT Developer also deploys compute/containers and configures device networking, which could include various edge gateway implementations. The IoT Developer implements designs for solutions to manage data pipelines, including monitoring and data transformation as it relates to IoT. The IoT Developer works with data engineers and other stakeholders to ensure successful business integration. IoT Developers should have a good understanding of Azure services, including data storage options, data analysis, data processing, and the Azure IoT PaaS versus SaaS options. After completing this course, students will be able to: Create, configure, and manage an Azure IoT hub. Provision devices by using IoT Hub and DPS, including provisioning at scale. Establish secure 2-way communication between devices and IoT Hub. Implement message processing by using IoT Hub routing and Azure Stream Analytics. Configure the connection to Time Series Insights and support business integration requirements. Implement IoT Edge scenarios using marketplace modules and various edge gateway patterns. Implement IoT Edge scenarios that require developing and deploying custom modules and containers. Implement device management using device twins and direct methods. Implement solution monitoring, logging, and diagnostics testing. Recognize and address security concerns and implement Azure Security Center for IoT. Build an IoT Solution by using Azure IoT Central and recongize SaaS opportunities for IoT. Course prerequisites IoT Developers should have basic programming skills in at least one Azure-supported language, including C#, Node.js, C, Python, or Java. Software development experience is a prerequisite for this course, but no specific software language is required, and the experience does not need to be at a professional level. Data Processing Experience: General understanding of data storage and data processing is a recommended but not required.  Cloud Solution Awareness: Students should have a basic understanding of PaaS, SaaS, and IaaS implementations. Microsoft Azure Fundamentals (M-AZ-900T00/M-AZ900), or equivalent skills, is recommended.  This course helps to prepare for exam AZ-220.   Agenda Module 1: Introduction to IoT and Azure IoT Services -Business Opportunities for IoT-Introduction to IoT Solution Architecture-IoT Hardware and Cloud Services Module 2: Devices and Device Communication -IoT Hub and Devices-IoT Developer Tools-Device Configuration and Communication Module 3: Device Provisioning at Scale -Device Provisioning Service Terms and Concepts-Configure and Manage the Device Provisioning Service-Device Provisioning Tasks Module 4: Message Processing and Analytics -Messages and Message Processing-Data Storage Options-Azure Stream Analytics Module 5: Insights and Business Integration -Business Integration for IoT Solutions-Data Visualization with Time Series Insights-Data Visualization with Power BI Module 6: Azure IoT Edge Deployment Process -Introduction to Azure IoT Edge-Edge Deployment Process-Edge Gateway Devices Module 7: Azure IoT Edge Modules and Containers -Develop Custom Edge Modules-Offline and Local Storage Module 8: Device Management -Introduction to IoT Device Management-Manage IoT and IoT Edge Devices-Device Management at Scale Module 9: Solution Testing, Diagnostics, and Logging -Monitoring and Logging-Troubleshooting Module 10: Azure Security Center and IoT Security Considerations -Security Fundamentals for IoT Solutions-Introduction to Azure Security Center for IoT-Enhance Protection with Azure Security Center for IoT Agents Module 11: Build an IoT Solution with IoT Central -Introduction to IoT Central-Create and Manage Device Templates-Manage Devices in Azure IoT Central [-]

MS-102: Microsoft 365 Administrator [-]

ISO/IEC 27005 Lead Risk Manager [-]

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. [-]

This course is ideal for individuals or teams who wish to build a solid understanding of ArchiMate 3 and develop architecture artifacts using ArchiMate. What's new in ArchiMate 3.0? Like ArchiMate 2, ArchiMate 3 is a comprehensive modeling language that allows architects to create commonly understood and integrated visualizations of the essential enterprise architecture domains. Published as an Open Group Standard in June 2016, the ArchiMate 3 specification is a major update to ArchiMate 2.1. New features in version 3 include:• New concepts - Strategy and Motivation• New entities – Application, Technology and Implementation layers• Better ways to connect planning with implementation• Improvements in cross-layer relationships• New ‘Physical’ layer• Improvements in the viewpoints definition mechanism   Examination Certification in ArchiMate requires you to pass both a Foundation exam and a Certified exam.The Foundation exam is a closed book, multiple choice exam consisting of 40 questions. There is a time limit of 60 minutes and the pass-rate is 60%.After passing the Foundation exam you can then move onto the Practitioner exam, which is an open book, multiple choice exam consisting of eight questions. There is a time limit of 90 minutes and the pass-rate is 70%.A number of exercises are interspersed throughout the course, which are aimed at testing your understanding and practical application of the training you have just received. At the end of the course, a number of mock-exam case study scenarios are provided which have been designed to simulate the actual exam.After passing both exams you will become a certified ArchiMate 3 Practitioner! [-]

Dette grunnleggende kurset om Microsoft Azure gir deg en solid forståelse av fundamentale konsepter i Azure-skymiljøet. Kursholderen, seniorutvikler John Inge Muldal Erlandsen, vil veilede deg gjennom nøkkelkomponentene og mulighetene som Azure tilbyr. Microsoft Azure er en ledende skyplattform og konkurrerer direkte med Amazon Web Services (AWS). Azure inneholder et bredt spekter av enheter, funksjoner og tjenester som du kan bruke for å oppfylle ulike behov innen skytjenester. Dette kurset er spesielt rettet mot forberedelse til AZ-900-eksamen, som fører til Microsoft-sertifiseringen "Microsoft Certified Fundamentals". Målet med kurset er å gi deg tilstrekkelig kunnskap og forberedelse til å bestå denne eksamenen med suksess. Kurset vil dekke følgende emner: Kapittel 1: Introduksjon Kapittel 2: Tjenester Kapittel 3: Verktøy Kapittel 4: Sikkerhet Kapittel 5: Styring Kapittel 6: Administrasjon Kapittel 7: Avslutning   Varighet: 4 timer og 32 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. [-]

Spring Boot Development [-]

Behersk kunsten å skape overbevisende presentasjoner med "PowerPoint: Komplett", et omfattende kurs ledet av Espen Faugstad hos Utdannet.no. Microsoft PowerPoint er en vital del av moderne kommunikasjon, brukt utstrakt i både næringslivet og utdanning. Dette kurset er designet for å gi deg fullstendig mestring av PowerPoint 2019, uansett om du er nybegynner eller ønsker å forbedre dine eksisterende ferdigheter. Kurset starter med grunnleggende, som å kjøpe og installere PowerPoint, og lærer deg å navigere i brukergrensesnittet. Du vil lære å lage presentasjoner som kombinerer tekst, bilder og illustrasjoner. Videre lærer kurset deg hvordan du kan lage din egen PowerPoint-mal, og bruker overganger og animasjoner for å gi presentasjonen din liv. Du vil også bli veiledet gjennom prosessen med å ferdigstille og holde en effektiv presentasjon. Ved kursets slutt vil du være i stand til å skape profesjonelle presentasjoner som engasjerer og informerer ditt publikum. Du vil ha en dyp forståelse av alle aspekter av PowerPoint, fra å lage innhold til å dele og presentere det på en effektiv måte.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Ny presentasjon Kapittel 3: Tekst Kapittel 4: Bilder Kapittel 5: Illustrasjoner Kapittel 6: Media Kapittel 7: Lysbildemal Kapittel 8: Overganger og animasjoner Kapittel 9: Ferdigstill presentasjon Kapittel 10: Start presentasjon Kapittel 11: Del presentasjon Kapittel 12: Avslutning   Varighet: 3 timer og 29 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Tjenesten fungerer på samme måte som strømmetjenester for musikk eller TV-serier. Våre kunder betaler en fast månedspris og får tilgang til alle kursene som er produsert så langt. Plattformen har hatt en god vekst de siste årene og kan skilte med 30.000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling moro, spennende og tilgjengelig for alle – og med oss har vi Innovasjon Norge og Forskningsrådet. [-]