Oversikt over relevante kurs innen Kurs i programvare og applikasjoner i Sør-Trøndelag

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 [-]

HENSIKTHensikten med kurset er å gi deltagerne en grunnleggende forståelse i bruken av tegne- og konstruksjonsprogrammet Autodesk Revit. Kurset er nødvendig for å komme raskt i gang med Autodesk Revit, og for å få den nødvendige forståelse for de mulighetene programmet gir. UTDANNINGSMÅLDu vil lære grunnleggende teknikk for bruk av programmet, og skal kunne bruke programmet til å lage 3D-modeller av bygninger, hente ut informasjon fra modellen og kunne produsere 2D-arbeidstegninger basert på 3D-modellen. KURSINNHOLD: Introduksjon av Autodesk Revit Architecture Brukergrensesnitt Behandling av visninger Oppretting av Etasjeplan og Rutenett Søyler Vegger, dører, vinduer Gulv/Himling Tak Editeringsverktøy Dimensjonering/Tekst/Tittelfelt Detaljering Utskrift Kurset er på norsk, men kursmanualen er engelsk. [-]

. 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 [-]

Synes du det er uoversiktlig å samarbeide om dokumenter med andre? Vi lærer deg de viktigste funksjonene og metodene for vellykket dokument-samhandling og ferdigstilling av dokumenter. 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:   Samarbeidsfunksjoner Spor endringer for å se hvem som har gjort hva Bruk av merknader Sammenligne dokumenter Passordbeskytte dokumenter   Filer i SharePoint, OneDrive for Business og OneDrive Samtidigredigering Versjonering   Før publisering Fjerne skjulte data Fjerne personlig informasjon   3 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Gratis support [-]

Microsoft 365 er abonnement på Office-programmer og andre produktivitetstjenester som du får tilgang til via Internett (skytjenester). Tidligere var dette kjent under navnet Office 365, men Microsoft har nå endret navnet til Microsoft 365. Fordelen er at du alltid har tilgang til Office-programmer og dine dokumenter, og kan dele dem med andre fra hvilken som helst enhet. Dette betyr at du har tilgang på dine dokumenter og verktøy via PC, mobil eller nettbrett. På kurset vil du lære om samhandling, kommunikasjon og tilgjengelighet. Om Microsoft 365Microsoft 365 er abonnement på Office-programmer og andre produktivitetstjenester som du får tilgang til via Internett (skytjenester). I abonnementet har du tilgang på en rekke applikasjoner, slik som Word, Excel, PowerPoint, Teams og lagring i OneDrive, samt mange andre nyttige verktøy. Fordelen er at du alltid har tilgang til Office-programmer og dine dokumenter, og kan dele dem med andre fra hvilken som helst enhet. Vi viser deg hvordan du kan jobbe effektivt med ditt Microsoft 365 abonnement. Pris: 1200 kroner Ansatte ved UiS har egne prisbetingelser.   Etter at du har meldt deg på webinaret, vil du få tilsendt praktisk informasjon om pålogging. Webinarene gjennomføres fra din PC eller nettbrett.    [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Ingen Innleveringer: 6 AV 10 øvinger må være godkjent for å kunne gå opp til eksamen. Vurderingsform: En individuell 4-timers nettbasert hjemmeeksamen. Ansvarlig: Svend Andreas Horgen Eksamensdato: 17.12.13 / 20.05.14         Læremål: KUNNSKAPER:Kandidaten:- kan forklare hva et program er- kan redegjøre for grunnleggende byggestener i programmering, så som variabler, kontrollstrukturer, matriser (arrays) og funksjoner- kan analysere en spesiell problemstilling og planlegge hvordan den kan løses generelt med programkode FERDIGHETER:Kandidaten:- kan bruke et .NET-basert utviklingsmiljø i kodeutvikling- kan lage funksjonelle brukergrensesnitt- kan identifisere feil i programkode- kan lage strukturert programkode som løser enkle problemstillinger- kan anvende innebygde funksjoner fra .NET-rammeverket i egen kode GENERELL KOMPETANSE:Kandidaten:- er bevisst på viktigheten av å eliminere feilsituasjoner Innhold:Introduksjon til grunnleggende programmeringsprinsipper som variabler, datatyper, kontrollstrukturer (løkker og beslutninger), matriser (arrays), egendefinerte funksjoner og innebyde funksjoner. Utforme brukergrensesnitt som er fine å se på og enkle å bruke. Feilhåndtering. Strukturere og planlegge koden på en god måte.Les mer om faget herDemo: Her er en introduksjonsvideo for faget Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Programmering i Visual Basic 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.  [-]

The course combines lecture with case studies to demonstrate basic architect design principles. Successful students have experience and knowledge in IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platforms, and governance. Students also have experience designing and architecting solutions. COURSE OBJECTIVES Skills gained Design a governance solution. Design a compute solution. Design an application architecture. COURSE CONTENT Module 1: Design compute and application solutions In this module you will learn about governance, compute, and application architectures. Lessons of Module 1 Design for governance Design for compute solutions Design for application architectures Lab : Case studies of Module 1 After completing this module, students will be able to: Design a governance solution. Design a compute solution. Design an application architecture. Module 2: Design storage solutions In this module, you will learn about non-relational storage, relational storage, and data integration solutions. Lessons of Module 2 Design a non-relational storage solution. Design a relational storage solution. Design a data integration solution. Lab : Case studies of Module 2 After completing this module, students will be able to: Design non-relational storage solutions. Design relational storage solutions. Design a data integration solution. Module 3: Design networking and access solutions In this module you will learn about authentication and authorization, identity and access for applications, and networking solutions. Lessons of Module 3 Design authentication and authorization solutions Design networking solutions Lab : Case studies of Module 3 After completing this module, students will be able to: Design authentication and authorization solutions. Design network solutions. Module 4: Design business continuity solutions Lessons of Module 4 Design for backup and disaster recovery Design monitoring solutions Design for migrations Lab : Case studies of Module 4 After completing this module, students will be able to: Design backup and disaster recovery. Design monitoring solutions. Design for migrations. [-]

COURSE OVERVIEW ou will learn how to configure and manage Cisco Nexus 9000 Series Switches in ACI mode, how to connect the Cisco ACI fabric to external networks and services, and fundamentals of Virtual Machine Manager (VMM) integration. You will gain hands-on practice implementing key capabilities such as fabric discovery, policies, connectivity, VMM integration, and more. This course is based on ACI Software v5.2 release.   This course helps you prepare to take the exam, Implementing Cisco Application Centric Infrastructure(300-620 DCACI), which leads to CCNP® Data Center and Cisco Certified Specialist – Data Center ACI Implementation certifications. TARGET AUDIENCE Individuals who need to understand how to configure and manage a data center network environment with the Cisco Nexus 9000 Switch operating in ACI Mode.   COURSE OBJECTIVES After completing this course, you should be able to: Describe Cisco ACI Fabric Infrastructure and basic Cisco ACI concepts Describe Cisco ACI policy model logical constructs Describe Cisco ACI basic packet forwarding Describe external network connectivity Describe VMM Integration Describe Layer 4 to Layer 7 integrations Explain Cisco ACI management features COURSE CONTENT Introducing Cisco ACI Fabric Infrastructure and Basic Concepts What Is Cisco ACI? Cisco ACI Topology and Hardware Cisco ACI Object Model Faults, Event Record, and Audit Log Cisco ACI Fabric Discovery Cisco ACI Access Policies Describing Cisco ACI Policy Model Logical Constructs Cisco ACI Logical Constructs Tenant Virtual Routing and Forwarding Bridge Domain Endpoint Group Application Profile Tenant Components Review Adding Bare-Metal Servers to Endpoint Groups Contracts Describing Cisco ACI Basic Packet Forwarding Endpoint Learning Basic Bridge Domain Configuration **** Introducing External Network Connectivity Cisco ACI External Connectivity Options External Layer 2 Network Connectivity External Layer 3 Network Connectivity Introducing VMM Integration VMware vCenter VDS Integration Resolution Immediacy in VMM Alternative VMM Integrations Describing Layer 4 to Layer 7 Integrations Service Appliance Insertion Without ACI L4-L7 Service Graph Service Appliance Insertion via ACI L4-L7 Service Graph Service Graph Configuration Workflow Service Graph PBR Introduction Explaining Cisco ACI Management Out-of-Band Management In-Band Management Syslog Simple Network Management Protocol Configuration Backup Authentication, Authorization, and Accounting Role-Based Access Control Cisco ACI Upgrade Collect Tech Support Labs Validate Fabric Discovery Configure Network Time Protocol (NTP) Create Access Policies and Virtual Port Channel (vPC) Enable Layer 2 Connectivity in the Same Endpoint Group (EPG) Enable Inter-EPG Layer 2 Connectivity Enable Inter-EPG Layer 3 Connectivity Compare Traffic Forwarding Methods in a Bridge Domain Configure External Layer 2 (L2Out) Connection Configure External Layer 3 (L3Out) Connection Integrate Application Policy Infrastructure Controller (APIC) With VMware vCenter Using VMware Distributed Virtual Switch (DVS) TEST CERTIFICATION Recommended as preparation for the following exams: 300-620 DCACI - Implementing Cisco Application Centric Infrastructure [-]

Det er utrolig hva du kan få til i Excel modeller ved å legge til enkel automatisering med Excel macro. Bli inspirert til å utforske de uendelige mulighetene Excel makroer gir! Webinaret kan også spesialtilpasses og holdes bedriftsinternt kun for din bedrift.   Kursinnhold:   Generelt om bruk av makro i Excel Åpne arbeidsbok med makro Kategori Utvikler og makroinnstillinger Innspiling av makro Innsetting av knapp i regnearket Enkelt redigering av kode Bruk av navngiving Bruk av If setning Bruk av MsgBox Lagre arbeidsbok med makro [-]

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

Ønsker du kontroll på ressursbruken din? Planlegg med ressurser og få en oversikt over hvor mange ressurser du trenger til enhver tid. Du kan også få en veldig god oversikt over økonomien i prosjektet.  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:   Hvilke typer ressurser har man tilgang på i Project Arbeidsressurser. Hvordan definere og bruke disse. Forskjell mellom generiske og personlige ressurser Materiellkostnader, hvordan benytte seg av dette i Project Hvordan sette opp kostnader   Ressursallokering i prosjektet Legge til, fjerne og endre ressurser Forskjellen mellom innsatsdreven og ikke innsatsdreven aktivitet Håndtere overallokeringer - hva skjer og hvordan få ressursplanlegging på plass   3 gode grunner til å delta 1. Få en oversikt over ressursbruk 2. Planlegg for bedre ressursbruk 3. Du får kontroll på utgiftene i prosjektet ditt   [-]

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     [-]

Kursinstruktør Terje Berg-Hansen Terje Berg-Hansen har bred erfaring fra prosjektledelse, utvikling og drift med små og store databaser, både SQL- og NoSQL-baserte. I tillegg til å undervise i etablerte teknologier leder han også Oslo Hadoop User Group, og er levende interessert i nye teknologier, distribuerte databaser og Big Data Science.    Kursinnhold XML er en moden standard for å utveksle informasjon mellom applikasjoner. Med XML og relaterte standarder som XSL(T) og XQuery er det mulig å utvikle distribuerte nettbaserte tjenester for utveksling av data i et standardisert format.    Målsetting Deltakerne vil etter kurset ha en grunnleggende forståelse av og kjennskap til hvorfor og hvordan XML kan anvendes for å oppnå en bedre utveksling og deling av strukturert og ustrukturert informasjon.   Forkunnskaper Grunnleggende kunnskaper om internett, HTML og CSS er en fordel, men ikke nødvendig for å ta dette kurset.   Kursinnhold Introduksjon Introduksjon til XML og XML-relaterte teknologier, som XPath, XQuery og XSL XML-verktøy Editorer og verktøy for validering, søk og endring av XML Grunnleggende XML XML struktur og syntaks. Gjennomgang av målene for XML. Lage og utforme XML dokumenter Navnerom (namespaces) Oppretting og bruk av navnerom for å skille elementer og funksjoner med samme navn. Validering av  XML Gjennomgang av teknologier som Document Type Definitions (DTD's) og XML Schemas for å kontrollere og styre struktur og data i XML filer Presentasjon av XML Bruk av html og CSS til å presentere XML data Søking i XML Søk i XML-dokumenter med XPath . Introduksjon til XSL(T) Kort om XSL og XSL Transformations. Bruk av XSLT til å formatere, sortere, filtrere og konvertere XML Data   Gjennomføring Kurset gjennomføres med en kombinasjon av online læremidler, gjennomgang av temaer og problemstillinger og praktiske øvelser. Det er ingen avsluttende eksamen, men det er øvelsesoppgaver til hovedtemaene som gjennomgås.   [-]

Bli en ekspert i å bruke WordPress, verdens mest populære publiseringssystem, med "WordPress: Komplett", et grundig kurs ledet av Espen Faugstad hos Utdannet.no. WordPress er en favoritt blant små og store bedrifter over hele verden og står bak en betydelig andel av nettsider på internett. Dette kurset er designet for å gi deg en omfattende forståelse av WordPress, fra grunnleggende installasjon til avansert tilpasning og administrasjon. Du vil starte med å lære hvordan du kjøper webhotell og domenenavn, og hvordan du laster opp og installerer WordPress ved hjelp av FTP-klienten FileZilla. Kurset dekker også tilpasning av utseendet på din WordPress-nettside, inkludert temaer og utvidelser, samt bruk av det innovative redigeringsverktøyet Gutenberg for å skape innhold. Du vil lære å opprette sider og blogginnlegg, administrere utvidelser og brukere, oversette temaer og utvidelser, og håndtere viktige innstillinger. Videre vil kurset guide deg gjennom hvordan du sikrer og oppdaterer din WordPress-nettside for å holde den trygg og funksjonell. Etter å ha fullført kurset, vil du ha ferdighetene og kunnskapen som trengs for å lage og vedlikeholde en profesjonell WordPress-nettside.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Installere WordPress Kapittel 3: Brukergrensesnitt Kapittel 4: Utseende Kapittel 5: Visuell redigering Kapittel 6: Sider Kapittel 7: Innlegg Kapittel 8: Utvidelser Kapittel 9: Brukere Kapittel 10: Oversette Kapittel 11: Innstillinger Kapittel 12: Sikkerhet Kapittel 13: Avslutning   Varighet: 3 timer og 46 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. [-]

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   [-]