Oversikt over relevante kurs innen IT-kurs i Buskerud

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

COURSE OVERVIEW Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. TARGET AUDIENCE The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure. COURSE OBJECTIVES   Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics COURSE CONTENT Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Introduction to Azure Synapse Analytics Describe Azure Databricks Introduction to Azure Data Lake storage Describe Delta Lake architecture Work with data streams by using Azure Stream Analytics Lab 1: Explore compute and storage options for data engineering workloads Combine streaming and batch processing with a single pipeline Organize the data lake into levels of file transformation Index data lake storage for query and workload acceleration After completing module 1, students will be able to: Describe Azure Synapse Analytics Describe Azure Databricks Describe Azure Data Lake storage Describe Delta Lake architecture Describe Azure Stream Analytics Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Design a multidimensional schema to optimize analytical workloads Code-free transformation at scale with Azure Data Factory Populate slowly changing dimensions in Azure Synapse Analytics pipelines Lab 2: Designing and Implementing the Serving Layer Design a star schema for analytical workloads Populate slowly changing dimensions with Azure Data Factory and mapping data flows After completing module 2, students will be able to: Design a star schema for analytical workloads Populate a slowly changing dimensions with Azure Data Factory and mapping data flows Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Lab 3: Data engineering considerations Managing files in an Azure data lake Securing files stored in an Azure data lake After completing module 3, students will be able to: Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Explore Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Lab 4: Run interactive queries using serverless SQL pools Query Parquet data with serverless SQL pools Create external tables for Parquet and CSV files Create views with serverless SQL pools Secure access to data in a data lake when using serverless SQL pools Configure data lake security using Role-Based Access Control (RBAC) and Access Control List After completing module 4, students will be able to: Understand Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Understand big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Lab 5: Explore, transform, and load data into the Data Warehouse using Apache Spark Perform Data Exploration in Synapse Studio Ingest data with Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Spark pools in Azure Synapse Analytics Integrate SQL and Spark pools in Azure Synapse Analytics After completing module 5, students will be able to: Describe big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Lab 6: Data Exploration and Transformation in Azure Databricks Use DataFrames in Azure Databricks to explore and filter data Cache a DataFrame for faster subsequent queries Remove duplicate data Manipulate date/time values Remove and rename DataFrame columns Aggregate data stored in a DataFrame After completing module 6, students will be able to: Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Lab 7: Ingest and load Data into the Data Warehouse Perform petabyte-scale ingestion with Azure Synapse Pipelines Import data with PolyBase and COPY using T-SQL Use data loading best practices in Azure Synapse Analytics After completing module 7, students will be able to: Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Data integration with Azure Data Factory or Azure Synapse Pipelines Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines Lab 8: Transform Data with Azure Data Factory or Azure Synapse Pipelines Execute code-free transformations at scale with Azure Synapse Pipelines Create data pipeline to import poorly formatted CSV files Create Mapping Data Flows After completing module 8, students will be able to: Perform data integration with Azure Data Factory Perform code-free transformation at scale with Azure Data Factory Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Orchestrate data movement and transformation in Azure Data Factory Lab 9: Orchestrate data movement and transformation in Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines After completing module 9, students will be able to: Orchestrate data movement and transformation in Azure Synapse Pipelines Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Lab 10: Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Understand developer features of Azure Synapse Analytics Optimize data warehouse query performance in Azure Synapse Analytics Improve query performance After completing module 10, students will be able to: Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Analyze and optimize data warehouse storage in Azure Synapse Analytics Lab 11: Analyze and Optimize Data Warehouse Storage Check for skewed data and space usage Understand column store storage details Study the impact of materialized views Explore rules for minimally logged operations After completing module 11, students will be able to: Analyze and optimize data warehouse storage in Azure Synapse Analytics Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark pools Query Azure Cosmos DB with serverless SQL pools Lab 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Synapse Analytics Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics After completing module 12, students will be able to: Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Lab 13: End-to-end security with Azure Synapse Analytics Secure Azure Synapse Analytics supporting infrastructure Secure the Azure Synapse Analytics workspace and managed services Secure Azure Synapse Analytics workspace data After completing module 13, students will be able to: Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Lab 14: Real-time Stream Processing with Stream Analytics Use Stream Analytics to process real-time data from Event Hubs Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics Scale the Azure Stream Analytics job to increase throughput through partitioning Repartition the stream input to optimize parallelization After completing module 14, students will be able to: Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Process streaming data with Azure Databricks structured streaming Lab 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks Explore key features and uses of Structured Streaming Stream data from a file and write it out to a distributed file system Use sliding windows to aggregate over chunks of data rather than all data Apply watermarking to remove stale data Connect to Event Hubs read and write streams After completing module 15, students will be able to: Process streaming data with Azure Databricks structured streaming Module 16: Build reports using Power BI integration with Azure Synpase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Create reports with Power BI using its integration with Azure Synapse Analytics Lab 16: Build reports using Power BI integration with Azure Synpase Analytics Integrate an Azure Synapse workspace and Power BI Optimize integration with Power BI Improve query performance with materialized views and result-set caching Visualize data with SQL serverless and create a Power BI report After completing module 16, students will be able to: Create reports with Power BI using its integration with Azure Synapse Analytics Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. Use the integrated machine learning process in Azure Synapse Analytics Lab 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics Create an Azure Machine Learning linked service Trigger an Auto ML experiment using data from a Spark table Enrich data using trained models Serve prediction results using Power BI After completing module 17, students will be able to: Use the integrated machine learning process in Azure Synapse Analytics     [-]

JOBB SMART OG EFFEKTIVT! E-læringskurset gir deg en opplevelsesrik og praktisk opplæring i e-postprogrammet Outlook 2016. En kombinasjon av videoer, teori, oppskrifter, oppgaver og tester gjør det enkelt å lære seg de nye funksjonene og verktøyene. E-læringskurset inneholder 46 opplæringsvideoer. E-læringskurset er tilpasset Office 365. * Office 365 gir deg alltid den nyeste versjonen av Outlook. * Navigasjonsfeltet gjør det enkelt å bytte mellom visningene i Outlook 2016. * Egen modus som er optimalisert for berøring. * Microsoft-kontoen kobler enheten til OneDrive, slik at du alltid har tilgang til filene dine. * Enklere søk etter kommandoer, handlinger og hjelp. * Mulighet for automatisk komprimering av store bildevedlegg. * Den første linjen i meldingsteksten vises som standard i meldingslisten og gir god oversikt. * Enklere filtrering av uleste meldinger. * Et integrert utskriftsmiljø med både utskriftsinnstillinger og forhåndsvisning. * Svarknapper gjør det enkelt å svare på eller videresende meldinger direkte fra leseruten. * Enklere sortering og gruppering av meldinger. * Hurtigtrinn kan brukes for å utføre flere handlinger samtidig. * Automatiske svar håndterer meldinger mens du er borte fra kontoret. * Møteinvitasjoner kan opprettes direkte basert på en melding. *Møteinvitasjoner viser et bilde av kalenderen, slik at du kan sjekke om du har ledig tid. * Personkortet i Outlook 2016 inneholder alle viktige detaljer om en kontakt samlet på ett sted. INNHOLDSFORTEGNELSE FØR DU STARTER Hva er Office 365? Elektronisk post Programvinduet Berøringsmodus Visninger Microsoft-konto Hjelp SENDING AV MELDINGER Nettetikette Sending av meldinger Meldingsformater Vedlegg Signatur Viktighet Svarknapper Leverings- og lesebekreftelse BEHANDLING AV MELDINGER Sending og mottak av meldinger Meldingslisten Bildenedlasting Forhåndsvisning og utskrift av meldinger Flagg for oppfølging Svar og videresending Sortering av meldinger Kolonner Direktesøk Organisering av meldinger Hurtigtrinn Søppelpost Automatiske svar KALENDER Kalenderen Avtaler Hendelser Møter Møtesvar Forhåndsvisning og utskrift av kalenderen Værdata PERSONER Kontakter Kontaktgrupper Forhåndsvisning og utskrift av kontakter OPPGAVER OG NOTATER Oppgaver Notater [-]

Sliter du med å importere data og lage rapporter/analysegrunnlag i Excel? Et riktig grunnlag er avgjørende for en god rapport! Se hvor enkelt man lager rapporter og analyserer data med Pivottabeller. Webinaret varer i 2 timer og består av to økter à 45 min. Etter hver økt er det 10 min spørsmålsrunde. Mellom øktene er det 10 min pause. Webinaret kan også spesialtilpasses og holdes bedriftsinternt kun for din bedrift.   Kursinnhold:   Import av tekstfil med problemer   Bruk veiviser for å importere tekstfil Fiks ulike problemstilling allerede i veiviser   Kort repetisjon av prinsipper om å arbeide med lister   Datavask - opprydding i grunnlaget Lær ulike metoder for å rydde opp i grunnlaget   Tabellfunksjonalitet Formater liste som tabell Bli kjent med fordeler å jobbe mot tabell Bli kjent med strukturere cellereferanser   Pivotteknikk [-]

COURSE OVERVIEW The course includes hands-on experience configuring, managing, and monitoring a firewall in a lab environment TARGET AUDIENCE This course is aimed at Security Engineers, Security Administrators, Security Operations Specialists, Security Analysts, and Support Staff. COURSE OBJECTIVES After you complete this course, you will be able to: Configure and manage the essential features of Palo Alto Networks next-generation firewalls Configure and manage Security and NAT policies to enable approved traffic to and from zones Configure and manage Threat Prevention strategies to block traffic from known and unknown IP addresses, domains, and URLs Monitor network traffic using the interactive web interface and firewall reports COURSE CONTENT 1 - Palo Alto Networks Portfolio and Architecture 2 - Configuring Initial Firewall Settings 3 - Managing Firewall Configurations 4 - Managing Firewall Administrator Accounts 5 - Connecting the Firewall to Production Networks with Security Zones 6 - Creating and Managing Security Policy Rules 7 - Creating and Managing NAT Policy Rules 8 - Controlling Application Usage with App-ID 9 - Blocking Known Threats Using Security Profiles 10 - Blocking Inappropriate Web Traffic with URL Filtering 11 - Blocking Unknown Threats with Wildfire 12 - Controlling Access to Network Resources with User-ID 13 - Using Decryption to Block Threats in Encrypted Traffic 14 - Locating Valuable Information Using Logs and Reports 15 - What's Next in Your Training and Certification Journey Supplemental Materials Securing Endpoints with GlobalProtect Providing Firewall Redundancy with High Availability Connecting Remotes Sites using VPNs Blocking Common Attacks Using Zone Protection   FURTHER INFORMATION Level: Introductory Duration: 5 days Format: Lecture and hands-on labs Platform support: Palo Alto Networks next-generation firewalls running PAN-OS® operating system version 11.0     [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Ingen Innleveringer: For å kunne gå opp til eksamen må 8 utvalgte øvingsoppgaver være godkjente. Personlig veileder: ja Vurderingsform: Skriftlig eksamen, individuell, 3 timer. Ansvarlig: Arne Bjørn Mikalsen Eksamensdato: 16.12.13 / 19.05.14         Læremål: KUNNSKAPERKandidaten:- kan gjøre rede for de mest brukte teknologiene for lokalnettverk- kan gjøre rede for teknisk oppbygning av nettverk- kan gjøre rede for ulike nettverkskomponenter, deres virkemåte og bruksområde- kan planlegge og vurdere sikkerhet i lokalnettverk FERDIGHETER:Kandidaten:- kan koble til og konfigurere en datamaskin slik at den fungerer i et nettverk med internettoppkobling- kan opprette brukerkontoer, tildele rettigheter, samt administrere nettverk med en ressursdatabase- kan planlegge, implementere og konfigurere et mindre lokalnettverk GENERELL KOMPETANSE:Kandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter innen emnets tema i en driftssituasjon- kan i en praktisk driftssituasjon, forklare og gjøre bruk av sin kunnskap både innen hvert enkelt tema i faget og på tvers av temaene- kan kommunisere med andre om nettverksløsninger Innhold:Fysiske medier i bruk i lokalnettverk. Nettverkskomponenter. Design av nettverk (nettverk infrastruktur). Trådløse nettverk, design og sikkerhet. Generelt om forskjellige typer nettverksoperativsystem. Introduksjon til Active Directory og eDirectory. Prinsipper for konfigurasjon, installasjon, drift og sikkerhet og driftsfilosofi i lokalnettverk. Introduksjon til virtualisering. Driftsmodeller: Fjerndrift eller ASP (Application Service Provider)Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Drift av lokalnettverk 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

COURSE OVERVIEW The Developing on Amazon Web Services AWS course is designed to help individuals design and build secure, reliable and scalable AWS-based applications. In this course, we cover fundamental concepts and baseline programming for developing applications on AWS. We also show you how to work with AWS code libraries, SDKs, and IDE toolkits so that you can effectively develop and deploy code on the AWS platform.   TARGET AUDIENCE This course is intended for Developers COURSE CONTENT Note: course outline may vary slightly based on the regional location and/or language in which the class is delivered. Day 1: Getting Started Working with the AWS code library, SDKs, and IDE toolkits Introduction to AWS security features Service object models and baseline concepts for working with Amazon Simple Storage Service (S3) and Amazon DynamoDB Day 2: Working with AWS Services Service object models and baseline concepts for working with the Amazon Simple Queue Service (SQS) and the Amazon Simple Notification Service (SNS) Applying AWS security features Day 3: Application Development and Deployment Best Practices Application deployment using AWS Elastic Beanstalk Best practices for working with AWS services   [-]

Trenger du en rask innføring i hvordan å lage en fremdriftsplan i Project? Delta på vårt webinar å se hvordan du kommer i gang med og lage en enkel fremdriftsplan. Webinaret varer i 2 timer og består av to økter à 45 min. Etter hver økt er det 10 min spørsmålsrunde. Mellom øktene er det 10 min pause. Webinaret kan også spesialtilpasses og holdes bedriftsinternt kun for din bedrift.   Kursinnhold:   Opprette prosjektkalender Se på unntak Se på tidsplan   Generelle innstillinger i Project   Opprette aktiviteter Enkel redigering av aktivitetslisten Disponere   Kobling av aktiviteter Tidsforskyvning Betingelsestyper   3 gode grunner til å delta 1. Få kontroll på prosjektkalenderen 2. Lær hvordan sette opp avhengighetsforhold mellom aktiviteter. 3. Hvorfor trenger vi en opprinnelig plan og hvordan opprette denne   [-]

Bli en mester i videoredigering med Adobe Premiere Pro gjennom dette dyptgående kurset ledet av Espen Faugstad, en erfaren kursholder hos Utdannet.no. Dette kurset krever ingen forkunnskaper og tar deg med fra grunnleggende til avanserte teknikker i Premiere Pro. Det er ideelt for alle som ønsker å lære profesjonell videoredigering, enten for personlig bruk eller for å utvikle karrieren som klipper. Kurset dekker alt fra opprettelse av prosjekter, organisering av filer, redigering av video og lyd, til bruk av effekter, overganger, og fargekorrigering. Du vil også lære å opprette titler, teksting, og bruke animasjon for å gi dine videoer et profesjonelt uttrykk. Ved kursets slutt vil du ha opparbeidet deg all den kunnskapen som trengs for å jobbe som en profesjonell videoredigerer.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Prosjekter Kapittel 3: Importere filer Kapittel 4: Redigere video Kapittel 5: Teknikker Kapittel 6: Redigere lyd Kapittel 7: Effekter og overganger Kapittel 8: Titler, grafikk og teksting Kapittel 9: Animere Kapittel 10: Fargekorrigere Kapittel 11: Eksportere Kapittel 12: Avslutning   Varighet: 6 timer og 5 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. [-]

Oracle GoldenGate 19c: Fundamentals for Oracle [-]

Due to the Coronavirus the course instructor is not able to come to Oslo. As an alternative we offer this course as a Blended Virtual Course.   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    The courseThis course provides essential skills for all mobile application testers. A mobile application is a software application designed to run on mobile devices such as smartphones and tablet computers. Mobile applications are becoming part of our every day lives and many organisations are developing applications to run on mobile devices to complement their desktop applications. This course will give the mobile application tester the knowledge skills needed to test mobile applications and to understand the differences and similarities in testing mobile applications to conventional applications. This course is highly practical - providing the participant with different mobile applications to test using a variety of techniques and tactics in order to find those mobile application bugs.The pre-requisite in receiving this qualification is that you have have attained the ISTQB Foundation.   The examThe Foundation Level Mobile Application Testing exam is comprised of 40 multiple-choice questions, with a pass mark grade of 65% to be completed within 60 minutes. Participants that take the exam not in their spoken language, will receive additional 25% time, for a total of 75 minutes. [-]

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

Blended Virtual Course The 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  This 3-day course is aimed at anyone wishing to attain the ISTQB Advanced Test Automation Engineer qualification. This qualification builds upon the Foundation syllabus and provides essential skills for all those involved in test automation and who want to develop further their expertise in one or more specific areas. Bouvet sine kursdeltakeres testresultater vs ISTQB gjennomsnitt A Test Automation Engineer is one who has broad knowledge of testing in general, and an in-depth understanding in the special area of test automation. An in-depth understanding is defined as having sufficient knowledge of test automation theory and practice to be able to influence the direction that an organization and/or project takes when designing, developing and maintaining test automation solutions for functional tests. The modules offered at the Advanced Level Specialist cover a wide range of testing topics.   The course is highly practical addressing the following areas: Introduction and objectives for Test Automation This section provides an introduction to test automation explaining the objectives, advantages, disadvantages and limitations of test automation as well as technical success factors of a test automation project. Preparing for Test Automation Understanding the type of system is vital for determining the most appropriate automation solution and also how we can design systems and testing for more effective automation. This section also looks at how we can evaluate for the most appropriate tools. The generic Test Automation architecture A test automation engineer has the role of designing, developing, implementing, and maintaining test automation solutions. As each solution is developed, similar tasks need to be done, similar questions need to be answered, and similar issues need to be addressed and prioritized. These reoccurring concepts, steps, and approaches in automating testing become the basis of the generic test automation architecture, and this will be discussed in detail during this section Deployment risks and contingencies This section looks at the various risks associated with the deployment of test tools and how to avoid test automation failure. Test Automation reporting and metrics Providing information to stakeholders for them to make informed decisions about the quality of the software is a vital part of testing and this section looks at the various metrics that can be used to monitor test automation and what information should be supplied to the stakeholder and how it should be presented. Transitioning manual testing to an automated environment This section looks at the various criteria to apply to determine the suitability for automation and understanding the factors for transitioning from manual to automation testing Verifying the Test Automation solution To have justified confidence in the information we supply to the stakeholders regarding test automation we must have justified confidence in the test environment and test automation solution supporting the information Continuous improvement This section looks ahead and how we can improve the automation solution making it more effective and efficient The Exam The ISTQB Advanced Test Automation Engineer exam is a 1 hour 30 minute, 40 question multiple-choice exam totaling 75 points. The pass mark is 65% (49 out of 75). It is a pre-requisite that attendees hold the ISTQB Foundation Level certificate. [-]

Få en gratis, effektiv og god innføring i Outlook! Lær hvordan du jobber med e-post, kalender, oppgaver og kontakter. Webinaret varer i 1 time og består av 1 økt à 45 min, samt 15 min spørsmålsrunde.   Kursinnhold:   Generelt Gjennomgang av båndet og programvinduet   E-post Tilpasse visningen for innboks og andre mapper Sende, svare på, og videresende e-post Legge til en signatur   Kalender Legge inn en avtale Legge inn en heldagshendelse Åpne kalenderen til kollegaer   Oppgaver Opprette en oppgave Følge opp e-post   Kontakter Opprette nye kontakter Lage en kontaktgruppe   Veien videre Se på flere muligheter i Outlook   [-]

Dette er et 4-dagers introduksjonskurs i Java-programmering. Kurset passer for deg som ønsker å komme igang med Java-programmering, forstå grunnleggende programmeringskonsepter, lage enkle programmer og forstå Java-kode skrevet av andre. Hvis du ikke har tatt noen Java-kurs tidligere er dette stedet å begynne. Vi bruker Eclipse IDE med siste versjon av Java (Standard Edition) til kurset.   Målsetting Etter gjennomført kurs vil deltakerne kunne skrive enkle programmer i Java og kjenne til de grunnleggende komponentene og prinsippene Java bygger på.   Kursinnhold Hva er Java? Kort historikk og anvendelseområder frem til idag. Grunnleggende konsepter for objektorientert programmering: Abstraksjon, innkapsling, arv og polymorfi Variabler og datatyper Klasser, objekter og metoder Public, Private og Protected Constructors, getters and setters Pakker og biblioteker Behandling av tall og tekst Betingelser (if - else, switch) Progammeringsløkker (for, while, do ... while, forEach) Lesing fra og skriving til tekstfiler Java Collections (Set, List, Map, ArrayList, TreeMap etc.) Lesing fra og skriving til databaser med JDBC Kompilering og eksekvering av Java-programmer Hente inn avhengigheter fra internett ved hjelp av Maven Nytt i Java: Stream api med filter, map, reduce, forEach og pil-funksjoner, samt Collections Literals.   Gjennomføring Kurset gjennomføres med en kombinasjon av online læringsmidler, gjennomgang av temaer og problemstillinger og praktiske øvelser. Det er ingen avsluttende eksamen, men det er øvingsoppgaver til hvert av temaene som gjennomgås. onsdag: Undervisning: Fra kl.10:00-14:00 + oppgaver som «hjemmelekse»torsdag: Undervisning: Fra kl.10:00-14:00 + oppgaver som «hjemmelekse»fredag: Undervisning: Fra kl.10:00-14:00 + oppgaver som «hjemmelekse»mandag: Gjennomgang og oppsummering Fra kl.10:00-14:00   [-]