Oversikt over relevante kurs innen Kurs i programvare og applikasjoner i Tromsø

Dette kurset tilbys som bedriftsinternt kurs   Fra mars 2020 til oktober 2020 økte antall daglige teams-brukere på verdensbasis fra 44 millioner til 115 millioner. Dette er en enorm økning og for mange innebar det å bli kastet inn i noe nytt uten opplæring. Det som egentlig skulle gjøre arbeidsdagen lettere, lagde flere utfordringer.  Appen er brukervennlig og fungerer sømløst med de andre verktøyene i Microsoft 365, men appen vokser ettersom behovene endrer seg, og med 115 millioner brukere er behovene også mange. Microsoft Teams er derfor et stort verktøy for god og effektiv samhandling, men verktøyene kan være så gode de bare vil – dersom de som bruker det ikke er kjent med funksjonalitetene som gjør Microsoft sømløst. I løpet av kurset vil deltagere få en god oversikt på hva Teams er, hva det kan brukes for, og hvordan best mulig bruke det. Kurset gir også tips og triks for best practice, samt hvordan man kan holde seg oppdatert på ny funksjonalitet som kommer.    Metode: Digitalkurs: Kursholder holder informative økter med gjennomgang og demonstrasjoner av de viktigste verktøyene, hvordan de virker sammen, og hvordan du og dine kollegaer bruker de effektivt sammen. Kursdeltakerne vil ha mulighet til å stille spørsmål, enten muntlig eller skriftlig, avhengig av gruppestørrelsen.    Kurs på Bouvethuset på Majorstuen: Kursholdere vil bruke en kombinasjon av undervisning, demonstrasjoner og øvelser så deltagerne kan raskt komme i gang og samtidig bygge en bevisst og robust tilnærming til verktøyet. Deltagkerne får da mulighet til å teste ut funksjonalitet underveis i Bouvet sitt kursmiljø.    Målgruppe Alle som ønsker en grundig introduksjon og opplæring i Teams applikasjonen. Det passer både for deg som aldri har brukt Teams før, og for deg som ønsker å utvikle deg til superbruker. Spesielt egnet for deg som skal være med å spesifisere, tilrettelegge eller være ansvarlig for innføring av samhandlingsløsninger.   Kursinnhold •    Teams som del av Office 365 plattformen•    Oversikt over begreper, lisensmodeller og relatert•    Pålogging, navigasjon og grensesnitt i Teams•    Hvordan strukturere velfungerende Teams: kanaler, faner, og mer•    Fillagring og fildeling•    Samtaler, chat og virtuelle møter•    Samtidig redigering•    Beste praksiser, tips og triks•    Innstillinger og sikkerhet•    Administrasjon for Teams eiere•    Kontinuerlig læring i bruk av verktøyet•    Samhandlingsstrategier   [-]

Er innboksen din et stort kaos? Bruker du mye tid på e-post? Vi viser deg hvordan du kan jobbe smart med innkommende og utgående kommunikasjon. 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:   Muligheter rundt e-post Alternativer og innstillinger for e-post Følge opp sendt e-post Automatisk håndtering av e-post ved hjelp av Hurtigtrinn og Regle   Søk og sortering Effektiv bruk av søk Søkemapper for hyppige og «komplekse» søk Visningsinnstillinger for å få fokus på det viktigste   Gjenbruk Lage maler for faste e-poster Opprette hurtigdeler for å kunne sette inn relevant innhold Bruk av distribusjonslister (grupper)   3 gode grunner til å delta 1. Se hvilke muligheter som er tilgjengelig knyttet til e-post 2. Du lærer å automatisere prosessering av e-post med regler og hurtigtrinn 3. Få tips til å bruke søk og søkemapper på en effektiv måte   [-]

Verden er i endring, det snakkes om den fjerde industrielle revolusjon og stadig flere ledere etterspør «radikal digital innovasjon». Men hva betyr det? Hvor skal vi begynne? Og hvordan kan vi sikre en plass med på toget inn i fremtiden, når vi lever i en virkelighet der teknologi utvikler seg eksponentielt og selskaper logaritmisk? Mange mener Design Thinking er svaret på det. Designtenking er et tankesett og en brukerorientert tilnærming til innovasjon. Metoden kombinerer designernes iterative tilnærming til tjeneste- og produktutvikling, med økonomenes analytiske og strategiske metoder for forretningsutvikling. Resultatet blir løsninger som har større sannsynlighet for å svare på brukerbehovene, er lønnsomme og i tråd med forretningsstrategi. Bli med på to dagers intensivt kurs i Design Thinking, lær å lage knallgode kundeopplevelser. Mål og gjennomføring Kurset er en blanding av praktisk workshop og foredrag med fokus på kundeopplevelse og de enorme digitale mulighetene vi har i dag. Med en «fail fast, fail cheap» tilnærming skal vi få kjenne på kroppen hva det betyr å ikke forelske seg i første idé, samarbeide på tvers av fagdisipliner og ikke minst ALLTID ha brukeren i fokus. Vi vil jobbe med å kartlegge kundens brukerbehov og jobber, og videre designe verdiforslag, tar valg, utforske gode forretningsmodell, teste, evaluerer og ikke minst LÆRE. Målet er at du skal forlate kurset med en verktøykasse du kan bruke på din egen arbeidsplass. Kurset inneholder: Forståelse av dagens digitale landskap Strategisk arbeid med innovasjon Design Thinking: teori og praktiske verktøy for design av verdifulle kundeopplevelser Kursleder: André Nordal Sylte, fagleder kundekonsept i DNB. Han jobber med å utforske og spesifisere prioriterte kundesegmenters viktigste behov, og designe verdiforslag til disse. Han har tidligere jobbet i Deloitte og Creuna. André er veldig kunnskapsrik og inspirerende, vi lover deg to meget lærerike og innholdsrike kvelder. Tid: 25. – 26. november kl. 17 – 21, matservering fra kl. 1630.   [-]

Ønsker du å mestre Google Analytics 4 for å få dybdeinnsikt i kundeadferden på nettstedet eller appen din? Da er kurset "Google Analytics 4: Komplett", ledet av Espen Faugstad, perfekt for deg. Dette kurset er designet for å gi deg en helhetlig forståelse av Google Analytics 4, slik at du kan jobbe profesjonelt med dette kraftige analyseverktøyet. Kurset starter med grunnleggende om hvordan Google Analytics 4 fungerer og veileder deg gjennom installasjonen på din nettside. Du vil lære å konfigurere Google Analytics for å maksimere dets potensial, administrere brukere, spore nettstedsøk, og mye mer. I tillegg gir kurset deg en detaljert gjennomgang av standardrapporter og utforskninger som er tilgjengelige i Google Analytics 4. Mot slutten av kurset vil du dykke inn i mer avanserte temaer som opprettelse og sporing av egendefinerte hendelser, konverteringssporing, og hvordan du kan utnytte innsikter fra brukerdata for å forbedre dine digitale strategier. Dette kurset er din vei til å bli en ekspert i Google Analytics 4.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Installer Kapittel 3: Konfigurer Kapittel 4: Rapporter Kapittel 5: Utforsk Kapittel 6: Hendelser Kapittel 7: Avansert Kapittel 8: Avslutning   Varighet: 4 timer og 48 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. [-]

Kursinnhold Import av .csv Import av tekstfiler (.txt) Import fra internett Transformering av data Rette opp feil Lage beregnede kolonner Regelmessig import Analyse av store datamengder   Det 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.   [-]

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     [-]

. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions.   TARGET AUDIENCE Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.   COURSE CONTENT Module 1: Creating Azure App Service Web Apps Students will learn how to build a web application on the Azure App Service platform. They will learn how the platform functions and how to create, configure, scale, secure, and deploy to the App Service platform. Azure App Service core concepts Creating an Azure App Service Web App Configuring and Monitoring App Service apps Scaling App Service apps Azure App Service staging environments Module 2: Implement Azure functions This module covers creating Functions apps, and how to integrate triggers and inputs/outputs in to the app. Azure Functions overview Developing Azure Functions Implement Durable Functions Module 3: Develop solutions that use blob storage Students will learn how Azure Blob storage works, how to manage data through the hot/cold/archive blob storage lifecycle, and how to use the Azure Blob storage client library to manage data and metadata. Azure Blob storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Module 4: Develop solutions that use Cosmos DB storage Students will learn how Cosmos DB is structured and how data consistency is managed. Students will also learn how to create Cosmos DB accounts and create databases, containers, and items by using a mix of the Azure Portal and the .NET SDK. Azure Cosmos DB overview Azure Cosmos DB data structure Working with Azure Cosmos DB resources and data Module 5: Implement IaaS solutions This module instructs students on how to use create VMs and container images to use in their solutions. It covers creating VMs, using ARM templates to automate resource deployment, create and manage Docker images, publishing an image to the Azure Container Registry, and running a container in Azure Container Instances. Provisioning VMs in Azure Create and deploy ARM templates Create container images for solutions Publish a container image to Azure Container Registry Create and run container images in Azure Container Instances Module 6: Implement user authentication and authorization Students will learn how to leverage the Microsoft Identity Platform v2.0 to manage authentication and access to resources. Students will also learn how to use the Microsoft Authentication Library and Microsoft Graph to authenticate a user and retrieve information stored in Azure, and how and when to use Shared Access Signatures. Microsoft Identity Platform v2.0 Authentication using the Microsoft Authentication Library Using Microsoft Graph Authorizing data operations in Azure Storage Module 7: Implement secure cloud solutions This module covers how to secure the information (keys, secrets, certificates) an application uses to access resources. It also covers securing application configuration information. Manage keys, secrets, and certificates by using the KeyVault API Implement Managed Identities for Azure resources Secure app configuration data by using Azure App Configuration Module 8: Implement API Management Students will learn how to publish APIs, create policies to manage information shared through the API, and to manage access to their APIs by using the Azure API Management service. API Management overview Defining policies for APIs Securing your APIs Module 9: Develop App Service Logic Apps This module teaches students how to use Azure Logic Apps to schedule, automate, and orchestrate tasks, business processes, workflows, and services across enterprises or organizations. Azure Logic Apps overview Creating custom connectors for Logic Apps Module 10: Develop event-based solutions Students will learn how to build applications with event-based architectures. Implement solutions that use Azure Event Grid Implement solutions that use Azure Event Hubs Implement solutions that use Azure Notification Hubs Module 11: Develop message-based solutions Students will learn how to build applications with message-based architectures. Implement solutions that use Azure Service Bus Implement solutions that use Azure Queue Storage queues Module 12: Monitor and optimize Azure solutions This module teaches students how to instrument their code for telemetry and how to analyze and troubleshoot their apps. Overview of monitoring in Azure Instrument an app for monitoring Analyzing and troubleshooting apps Implement code that handles transient faults Module 13: Integrate caching and content delivery within solutions Students will learn how to use different caching services to improve the performance of their apps. Develop for Azure Cache for Redis Develop for storage on CDNs [-]

Stadig flere bedrifter har behov for folk med kunnskaper om data og databehandling. Kan du dokumentere at du har slik kunnskap? Mål med kurset: Deltakeren skal tilegne seg kunnskaper om de mest benyttede Windows programmene og etter avsluttet kurs kunne jobbe smartere og mer effektivt. Krav til forkunnskaper: Et innføringskurs i data eller noe erfaring med data fra før er nødvendig. Kurset MS Office 2016 - 4 Moduler tar for seg de mest brukte Windows programmene: Excel Word PowerPoint Windows 10 Gjennomføring:  Gjennomføres på Internett, interaktivt. Kurset inneholder tekst, bilder, videofremvisninger, små tester og en mengde oppgaver. Enkelt og fleksibelt. Kursdeltageren har on-line tilgang i 12 måneder fra man starter å ta kurset.  Dette gjør at man har tilstrekkelig tid til å tilegne seg nødvendige kunnskaper. [-]

E-læringskurset gir deg en opplevelsesrik og praktisk opplæring i regnearkprogrammet Excel 2016. En kombinasjon av videoer, teori, oppskrifter, oppgaver og tester gjør det enkelt å lære seg de nye verktøyene. E-læringskurset inneholder 59 opplæringsvideoer.E-læringskurset er tilpasset Office 365.Testene i e-læringskurset måler kunnskap før, under og etter opplæringen. Når ettertesten er bestått får du tilgang til et kursbevis i PDF-format som enkelt kan lagres eller skrives ut.Jobb smart og effektivt!- Office 365 gir deg alltid den nyeste versjonen av Excel.- Maler er tilgjengelig ved oppstart.- Enklere åpning og lagring av arbeidsbøker.- Microsoft-kontoen kobler enheten til OneDrive, slik at du alltid har tilgang til filene dine.- Egen modus som er optimalisert for berøring.- Enklere søk etter kommandoer, handlinger og hjelp.- Formler utfører beregninger raskt og enkelt.- Autofyll forenkler arbeidet med å fylle inn data i et regneark.- Håndskriftsformler gjør det enklere å skrive inn formler for hånd.- Cellestiler gjør formateringen mer konsekvent.- Bruk av tema gir en konsekvent layout på alle Office-dokumenter.- Betinget formatering gjør det enkelt å følge med sentrale verdier i regnearket.- Hurtiganalyse gjør det raskt og enkelt å tolke og analysere et dataområde.- Du har tilgang til et utall ferdigdefinerte funksjoner som utfører alle slags beregninger.- Diagram egner seg godt for å gi et visuelt, lettfattelig inntrykk av tallverdier.- Sparkline-grafikk kan brukes for å visualisere data direkte i regnearkceller.- Sortering og filtrering gjør arbeidet med lister og tabeller enkelt og effektivt.- Bruk av flere regneark gjør større regnearkmodeller mer oversiktlig.- Et integrert utskriftsmiljø med både utskriftsinnstillinger og forhåndsvisning.Innhold:- Før du starter- Redigering- Formler- Formatering- Funksjoner- Diagram- Lister og tabeller- Flere regneark- UtskriftKURSET KAN KJØRES PÅ NETTBRETT! [-]

Jira Service Management Essentials (Cloud) [-]

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. [-]

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

AZ-400: Designing and Implementing Microsoft DevOps solutions [-]

COURSE OVERVIEW . This training collection gives you the hands-on skills to deliver virtual desktops and applications through a single virtual desktop infrastructure platform. You will build on your skills in configuring and managing VMware Horizon® 8 through a combination of lecture and hands-on labs. You learn how to configure and deploy pools of virtual machines and how to provide a customized desktop environment to end-users. Additionally, you will learn how to install and configure a virtual desktop infrastructure platform. You learn how to install and configure VMware Horizon® Connection Server™, VMware Unified Access Gateway™, how to configure a load balancer for use with Horizon, and how to establish Cloud Pod Architecture.  Product Alignment: VMware Horizon 8 V2006 TARGET AUDIENCE Operators, administrators, and architects for VMware Horizon should enroll in this course. These individuals are responsible for the creation, maintenance, and or delivery of remote and virtual desktop services. Additional duties can include the implementation, support, and administration of an organization's end-user computing infrastructure. COURSE OBJECTIVES By the end of the course, you should be able to meet the following objectives: Recognize the features and benefits of Horizon Use VMware vSphere® to create VMs to be used as desktops for Horizon Create and optimize Windows VMs to create Horizon desktops Install and configure Horizon Agent on Horizon desktop Configure and manage the VMware Horizon® Client™ systems and connect the client to a VMware Horizon desktop Configure, manage, and entitle desktop pools of full VMs Configure, manage, and entitle pools of instant-clone desktops Create and use Remote Desktop Services (RDS) desktops and application pools Monitor the Horizon environment using Horizon Console Dashboard and Horizon Help Desk Tool Identify Horizon Connection Server installation, architecture, and requirements. Describe the authentication and certification options for a Horizon environment Recognize the integration process and benefits of VMware Workspace ONE® Access™ and Horizon 8 Discuss performance and scalability options available in Horizon 8 Describe different security options for the Horizon environment COURSE CONTENT 1  Course Introduction Introductions and course logistics Course objectives 2  Introduction to VMware Horizon Recognize the features and benefits of Horizon Describe the conceptual and logical architecture of Horizon 3  Introduction to Use Case Define a use case for your virtual desktop and application infrastructure Convert customer requirements to use-case attributes 4  vSphere for Horizon 8 Explain basic virtualization concepts Use VMware vSphere® Client™ to access your vCenter Server system and VMware ESXi™ hosts Create, provision, and remove a virtual machine 5  VMware Horizon Desktops Create a Windows and a Linux virtual machine using vSphere Optimize and prepare Windows and Linux virtual machines to set up Horizon desktop VMs 6  VMware Horizon Agents Outline the configuration choices when installing Horizon Agent on Windows and Linux virtual machines Create a gold master for Windows Horizon desktops 7  VMware Horizon Pools Identify the steps to set up a template for desktop pool deployment List the steps to add desktops to the VMware Horizon® Connection Server™ inventory Compare dedicated-assignment and floating-assignment pools Outline the steps to create an automated pool Define user entitlement Explain the hierarchy of global, pool-level, and user-level policies 8  VMware Horizon Client Options Describe the different clients and their benefits Access Horizon desktop using various Horizon clients and HTML Configure integrated printing, USB redirection, and the shared folders option Configure session collaboration and media optimization for Microsoft Teams 9  Creating and Managing Instant-Clone Desktop Pools List the advantages of instant clones Explain the provisioning technology used for instant clone desktop pools Set up an automated pool of instant clones Push updated images to instant clone desktop pools 10  Creating RDS Desktop and Application Pools Explain the difference between an RDS desktop pool and an automated pool Compare and contrast an RDS session host pool, a farm, and an application pool Create an RDS desktop pool and an application pool Access RDS desktops and application from Horizon Client Use the instant clone technology to automate the build-out of RDSH farms Configure load-balancing for RDSHs on a farm 11  Monitoring VMware Horizon Monitor the status of the Horizon components using the Horizon Administrator console dashboard Monitor desktop sessions using the HelpDesk tool 12  Course Introduction Introductions and course logistics Course objectives 13  Horizon Connection Server Recognize VMware Horizon reference architecture Identify the Horizon Connection Server supported features Identify the recommended system requirements for Horizon Connection Server Configure the Horizon event database Outline the steps for the initial configuration of Horizon Connection Server Discuss the ADAM database as a critical component of Horizon Connection Server installation 14  VMware Horizon Authentication and Certificates Compare the authentication options that Horizon Connection Server supports Describe the Smartcard authentication options that Horizon Connection Server supports Outline the steps to create a Horizon administrator and custom roles Describe the roles available in a Horizon environment Explain the role that certificates play for Horizon Connection Server Install and configure certificates for Horizon Connection Server Install and configure True SSO in a Horizon environment 15  Workspace ONE Access & Virtual Application Management Recognize the features and benefits of Workspace ONE Access Recognize the Workspace ONE Access console features Explain identity management in Workspace ONE Access Explain access management in Workspace ONE Access Describe the Workspace ONE Access directory integration Describe the Workspace ONE Access directory integration Deploy virtual applications with Workspace services 16  VMware Horizon Performance and Scalability Describe the purpose of a replica connection server Explain how multiple Horizon Connection Server instances in a pod maintain synchronization Describe the 3D rendering options available in Horizon 8 List the steps to configure graphics cards for use in a Horizon environment Configure a load balancer for use in a Horizon environment Explain Horizon Cloud Pod Architecture LDAP replication and VIPA Explain Horizon Cloud Pod Architecture scalability options 17  Managing VMware Horizon Security Explain concepts relevant to secure Horizon connections Describe how to restrict Horizon connections. Discuss the benefits of using Unified Access Gateway List the two-factor authentication options that are supported by Unified Access Gateway List Unified Access Gateway firewall rules Describe the situation in which you might deploy Unified Access Gateway instances with one, two, or three network interfaces TEST CERTIFICATION VMware Certified Professional – Desktop and Mobility 2020 (VCP-DTM 2020) [-]

AI-900: Microsoft Azure AI Fundamentals [-]