Oversikt over relevante kurs innen IT-kurs i Krødsherad

Kurset fokuserer på integrering av forskjellige verdistrømmer og aktiviteter for å lage, levere og støtte IT-aktiverte produkter og tjenester, samtidig som den dekker støtte for praksis, metoder og verktøy. Kurset gir kandidatene forståelse for tjenestekvalitet og forbedringsmetoder. E-læringskurset inneholder 18 timer med undervisning, og er delt inn i 8 moduler. Les mer om ITIL® 4 på AXELOS sine websider. Inkluderer: Tilgang til ITIL® 4 Specialist: Create, Deliver and Support e-læring (engelsk) i 12 måneder. ITIL® 4 Specialist: Create, Deliver and Support online voucher til sertifiseringstest.   ITIL®/PRINCE2®/MSP®/MoP® are registered trademarks of AXELOS Limited, used under permission of AXELOS Limited. All rights reserved. [-]

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 [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Du må ha god kjennskap til Windows 2008 server og oppsett av AD og DNS og installasjon av SQL 2008 server. For deg som ikke har kjennskap til Windows 2008 server og/eller som heller vil bruke mer tid på SharePoint kan vi tilby en variant der du får ferdig oppsatte servere og SharePoint installert. Innleveringer: 8 obligatoriske øvinger. Personlig veileder: ja Vurderingsform: 2 dagers praktisk hjemmeeksamen med både teoretiske og praktiske oppgaver. Ansvarlig: Stein Meisingseth Eksamensdato: 19.12.13 / 15.05.14         Læremål: KUNNSKAPER:Kandidaten må:- kjenne til bruken av SharePoint i forskjellige situasjoner i en bedrift/organisasjon- kunne gjøre rede for hvordan SharePoint brukes i samskriving- kunne beskrive hvordan ulike roller i en organisasjon kan bruke SharePoint- ha kjennskap til hva det vil si å ha ansvaret for bruken av SharePoint i en bedrift/organisasjon FERDIGHETER:Kandidaten må:- kunne opprette webområder for deling av informasjon med andre- kunne sette opp administrasjon av dokumenter- kunne sette opp publisering av rapporter- kunne sette opp sidestruktur og brukerrettigheter, sideoppsett og tillatelser- kunne opprette infrastruktur for webområder- kunne sette opp muligheter for søking- kunne konfigurere systemet for bruk fra Internett- kunne konfigurerer Office Web Apps- kunne sette opp muligheter for å benytte arbeidsflyt GENERELL KOMPETANSE:Kandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter i en bedrift som vil bruke SharePoint- kan i et praktisk prosjekt forklare og gjøre bruk av sin kunnskap for bruk av SharePoint Innhold:Hva er SharePoint. Roller. Tilgang til SharePoint. Opprette og bruke Team Sites. Navigering. Lister og Libraries. Home page. Opprette og bruke webpart. Opprette og bruke SharePoint Sites and Site Collections. Opprette og bruke maler. Sikkerhet i SharePoint. Opprette og bruke Wiki. Dokumentdeling. Søking.Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag SharePoint 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

Microsoft 365 Enterprise Administrator Expert (MCE) - Boot Camp [-]

Bedriftstilbud! Vi tilbyr nå rabatterte priser for på PECB ISO/IEC Foundation 27001 som bedriftsinternt kurs for grupper (minimum 5 personer).Kurset kan holdes i lokalene til Orange Cyberdefense på Lysaker Torg, eller hos dere. Kontakt oss for et godt tilbud.  Har dere sikkerhetskompetansen dere trenger? Orange Cyberdefense holder sertifiseringskurs innen cyber- og informasjonssikkerhet levert av den anerkjente sertifisering- og kursleverandøren PECB. PECB ISO/IEC 27001 Foundation er et 2 dagers kurs, der man vil lære om de grunnleggende elementene for å implementere og lede et styringssystem for informasjonssikkerhet (ISMS) i samsvar med ISO/IEC 27001. Etter kurset vil kursdeltagerne forstå de ulike delene i et ISMS, inkludert policyer, rutiner, måling, internrevisjon og kontinuerlig forbedring. Kurset er ment for bedriftens ansatte som skal delta i innføringen av et styringssystem for informasjonssikkerhet, eller som trenger å lære mer om informasjonssikkerhet og styring av dette i en virksomhet.  Læringsmål for kurset Kjennskap til ISO/IEC 27001 og kunne se sammenhenger mellom ISO/IEC 27001, ISO/IEC 27002 og andre rammeverk. Forstå ulike tilnærminger, standarder, metoder og teknikker som brukes for å implementere og styre et ISMS. Kunne drifte elementene i et styringssystem for informasjonssikkerhet ISMS.   Bindende påmelding Vi forbeholder oss retten til å utsette kurs ved for få deltakere/ påmeldte. Tilbud om ny kursdato vil bli gitt.  [-]

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 etablert standard for plattformuavhengig lagring og utveksling av data, der innhold og presentasjon bearbeides separat. XSL er en nøkkelteknologi innenfor utvikling og nyttiggjørelse av XML. Viktige hoveddeler innenfor XSL er XSLT, XSL-FO og XPath. Kurset gir deltakerne en innføring i XSL . Vi ser på hvilke muligheter vi har for bearbeiding av XML-data, og hvordan vi kan gjøre data tilgjengelig for presentasjon.   Du får en gjennomgang i: Introduksjon til XML, XSL og XSLT. Introduksjon til XPath og XQuery. Bruk av XSLT-maler og Xpath-uttrykk for å søke etter data i XML-dokumenter. Transformering av XML-dokumenter til xml, html og tekstdokumenter. Introduksjon til XSL-FO og produksjon av svg- og pdf-dokumenter Design og formatering av ouput fra XSLT-transformasjoner Sortering, gruppering og kombinering av XML-dokumenter Bruk av XSLT-verktøy til transformering og søk.   Målsetting Etter endt kurs skal kursdeltakerne blant annet vite hvordan man filtrerer, sorterer og transformerer XML-data, samt hvilke muligheter man har for å trekke inn annet innhold/data for presentasjon.   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.   [-]

COURSE OVERVIEW  You will learn to deliver secure remote access to apps and desktops integrating Citrix Virtual Apps and Citrix Desktops with Citrix Gateway.  This course includes an exam. TARGET AUDIENCE Built for IT Professionals working with Citrix ADC and Gateway, with little or no previous Citrix networking experience. Potential students include administrators, engineers, and architects interested in learning how to deploy or manage Citrix ADC or Citrix Gateway environments. COURSE OBJECTIVES  Identify the functionality and capabilities of Citrix ADC and Citrix Gateway Explain basic Citrix ADC and Gateway network architecture Identify the steps and components to secure Citrix ADC Configure Authentication, Authorization, and Auditing Integrate Citrix Gateway with Citrix Virtual Apps, Citrix Virtual Desktops and other Citrix components COURSE CONTENT Module 1: Getting Started Introduction to Citrix ADC Feature and Platform Overview Deployment Options Architectural Overview Setup and Management Module 2: Basic Networking Networking Topology Citrix ADC Components Routing Access Control Lists Module 3: ADC Platforms Citrix ADC MPX Citrix ADC VPX Citrix ADC CPX Citrix ADC SDX Citrix ADC BLX Module 4: High Availability Citrix ADC High Availability High Availability Configuration Managing High Availability In Service Software Upgrade Troubleshooting High Availability Module 5: Load balancing Load Balancing Overview Load Balancing Methods and Monitors Load Balancing Traffic Types Load Balancing Protection Priority Load Balancing Load Balancing Troubleshooting Module 6: SSL Offloading SSL Overview SSL Configuration SSL Offload Troubleshooting SSL Offload SSL Vulnerabilities and Protections Module 7: Security Authentication, Authorization, and Auditing Configuring External Authentication Admin Partitions Module 8: Monitoring and Troubleshooting Citrix ADC Logging Monitoring with SNMP Reporting and Diagnostics AppFlow Functions Citrix Application Delivery Management Troubleshooting Module 9: Citrix Gateway Introduction to Citrix Gateway Advantages and Utilities of Citrix Gateway Citrix Gateway Configuration Common Deployments Module 10: AppExpert Expressions Introduction to AppExpert Policies Default Policies Explore Citrix ADC Gateway Policies Policy Bind Points Using AppExpert with Citrix Gateway Module 11: Authentication, Authorization, and Secure Web Gateway Authentication and Authorization Multi-Factor Authentication nFactor Visualizer SAML authentication Module 12: Managing Client Connections Introduction to Client Connections Session Policies and Profiles Pre and Post Authentication Policies Citrix Gateway Deployment Options Managing User Sessions Module 13: Integration for Citrix Virtual Apps and Desktops Virtual Apps and Desktop Integration Citrix Gateway Integration Citrix Gateway WebFront ICA Proxy Clientless Access and Workspace App Access Fallback SmartControl and SmartAccess for ICA Module 14: Configuring Citrix Gateway Working with Apps on Citrix Gateway RDP Proxy Portal Themes and EULA [-]

Mange av prinsippene for stor dokumenter kan med fordel også anvendes på de aller fleste dokumenter, inklusive brev og notater. Her går vi gjennom alt du trenger for å skrive bøker eller avhandlinger og også det du trenger for å skrive invitasjoner til nyttårsfest eller barnebursdag. Kursinnhold Fletting til brev, konvolutter, etiketter og e-post Bruk av stiler Bilder og bildetekster innholdsfortegnelse, stikkordliste og figurliste Spalter, marger, sidefarger, sidekantlinjer og dokumenttemaer. Deldokumenter kan samles i et hoved dokument  Topp- og bunntekster og side nummerering. Utklipp, figurer, SmartArt og diagram. Tekstbokser Tabeller: Formatering, sortering og beregninger. Maler med Felt, innholdskontroller og skjemakontroller Med makroer kan du effektivisere avanserte oppgaver som består av serie med handlinger. 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. [-]

Dette webinaret fokuserer på bruk av eksisterende presentasjoner, endringer av disse, samt det å klargjøre for presentasjon. Vi viser deg en rekke tips og teknikker som bidrar til at presentasjonen ser strøken ut, og som hjelper deg å spare verdifull tid i forberedelsesfasen.  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:   Gjenbruk Sette inn lysbilder fra andre presentasjoner Tilbakestille lysbildeoppsett Endre mal Rydde opp i manuelle feil   Klargjøring Konvertere tekst til SmartArt Animasjon og lysbildeovergang Tilrettelegge for navigasjon (hyperkoblinger) Tilpasset fremvisning Lag lysbildefremvisning Ta med presentasjonen på minnepinne   3 gode grunner til å delta 1. Lær og gjenbruke innhold fra andre presentasjoner effektivt 2. Få oversikt over måter å "rydde opp" i en presentasjon 3. Få tips til praktiske verktøy til ferdigstilling av presentasjonen   [-]

COURSE OVERVIEW  This course covers the process of designing, implementing, and managing core Azure networking infrastructure, Hybrid Networking connections, load balancing traffic, network routing, private access to Azure services, network security and monitoring. Learn how to design and implement a secure, reliable, network infrastructure in Azure and how to establish hybrid connectivity, routing, private access to Azure services, and monitoring in Azure. TARGET AUDIENCE This course is aimed at Network Engineers looking to specialize in Azure networking solutions. An Azure Network engineer designs and implements core Azure networking infrastructure, hybrid networking connections, load balance traffic, network routing, private access to Azure services, network security and monitoring. The azure network engineer will manage networking solutions for optimal performance, resiliency, scale, and security. COURSE CONTENT Module 1: Azure Virtual Networks In this module you will learn how to design and implement fundamental Azure Networking resources such as virtual networks, public and private IPs, DNS, virtual network peering, routing, and Azure Virtual NAT. Azure Virtual Networks Public IP Services Public and Private DNS Cross-VNet connectivity Virtual Network Routing Azure virtual Network NAT Lab 1: Design and implement a Virtual Network in Azure Lab 2: Configure DNS settings in Azure Lab 3: Connect Virtual Networks with Peering After completing module 1, students will be able to: Implement virtual networks Configure public IP services Configure private and public DNS zones Design and implement cross-VNET connectivity Implement virtual network routing Design and implement an Azure Virtual Network NAT   Module 2: Design and Implement Hybrid Networking In this module you will learn how to design and implement hybrid networking solutions such as Site-to-Site VPN connections, Point-to-Site VPN connections, Azure Virtual WAN and Virtual WAN hubs. Site-to-site VPN connection Point-to-Site VP connections Azure Virtual WAN Lab 4: Create and configure a local gateway Create and configure a virtual network gateway Create a Virtual WAN by using Azure Portal Design and implement a site-to-site VPN connection Design and implement a point-to-site VPN connection Design and implement authentication Design and implement Azure Virtual WAN Resources   Module 3: Design and implement Azure ExpressRoute In this module you will learn how to design and implement Azure ExpressRoute, ExpressRoute Global Reach, ExpressRoute FastPath and ExpressRoute Peering options. ExpressRoute ExpressRoute Direct ExpressRoute FastPath ExpressRoute Peering Lab 5: Create and configure ExpressRoute Design and implement Expressroute Design and implement Expressroute Direct Design and implement Expressroute FastPath   Module 4: load balancing non-HTTP(S) traffic in Azure In this module you will learn how to design and implement load balancing solutions for non-HTTP(S) traffic in Azure with Azure Load balancer and Traffic Manager. Content Delivery and Load Blancing Azure Load balancer Azure Traffic Manager Azure Monitor Network Watcher Lab 6: Create and configure a public load balancer to load balance VMs using the Azure portal Lab:7 Create a Traffic Manager Profile using the Azure portal Lab 8: Create, view, and manage metric alerts in Azure Monitor Design and implement Azure Laod Balancers Design and implement Azure Traffic Manager Monitor Networks with Azure Monitor Use Network Watcher   Module 5: Load balancing HTTP(S) traffic in Azure In this module you will learn how to design and implement load balancing solutions for HTTP(S) traffic in Azure with Azure Application gateway and Azure Front Door. Azure Application Gateway Azure Front Door Lab 9: Create a Front Door for a highly available web application using the Azure portal Lab 10: Create and Configure an Application Gateway Design and implement Azure Application Gateway Implement Azure Front Door   Module 6: Design and implement network security In this module you will learn to design and imponent network security solutions such as Azure DDoS, Azure Firewalls, Network Security Groups, and Web Application Firewall. Azure DDoS Protection Azure Firewall Network Security Groups Web Application Firewall on Azure Front Door Lab 11: Create a Virtual Network with DDoS protection plan Lab 12: Deploy and Configure Azure Firewall Lab 13: Create a Web Application Firewall policy on Azure Front Door Configure and monitor an Azure DDoS protection plan implement and manage Azure Firewall Implement network security groups Implement a web application firewall (WAF) on Azure Front Door   Module 7: Design and implement private access to Azure Services In this module you will learn to design and implement private access to Azure Services with Azure Private Link, and virtual network service endpoints. Define Azure Private Link and private endpoints Design and Configure Private Endpoints Integrate a Private Link with DNS and on-premises clients Create, configure, and provide access to Service Endpoints Configure VNET integration for App Service Lab 14: restrict network access to PaaS resources with virtual network service endpoints Lab 15: create an Azure private endpoint Define the difference between Private Link Service and private endpoints Design and configure private endpoints Explain virtual network service endpoints Design and configure access to service endpoints Integrate Private Link with DNS Integrate your App Service with Azure virtual networks   TEST CERTIFICATION This course helps to prepare for exam AZ-700 [-]

Vi gir deg Excel kurs gratis, få en effektiv og god innføring i Excel! Godt egnet for deg som ikke kjenner til så mye mer enn Summer-knappen, og ønsker å utvide horisonten litt. Om du trenger Excel hjelp, er vårt online Excel kurs på nett stedet å starte.   Kursinnhold:   Gjennomgang av båndet, programvinduet og viktige begreper  Kategorier, grupper, knapper, dialogboksvelger Vise / skjule båndet Navneboks, formlinje, statuslinje m.m.   Nyttig bruk av autofyll  Lage serier med ukedager og måneder Autofylle tall og datoer Kopiere tekst, tall, format, formler og funksjoner   Lage et enkelt «privatbudsjett»  Forklaring av de grunnleggende konseptene i Excel Funksjoner som SUMMER, GJENNOMSNITT Formatering av utsende   Grafisk fremstilling av data - stolpe diagram  Grunnleggende gjennomgang av diagramverktøy Oppdatering av data   Veien videre  Se hvor enkelt kan du opprette rapporter ved å bruke tabellfunksjonalitet og filter Se hvor raskt kan du opprette rapporter ved å bruke Pivottabell [-]

Kurs i cybersikkerhet med Carsten Maartmann-Moe. Du lærer om cyberkriminelle,  og de største risikoene for angrep. Cybersikkerhet eller IT-sikkerhet er i nyhetene nesten hver dag, men hva er fakta og hva er fiksjon? Kan du bli hacket når som helst? Er alle ute etter din virksomhet? Hva er de største risikoene, og hvordan kan man effektivt redusere dem? I dette kurset lærer du hvordan cyberkriminelle opererer, hva de største risikoene er, og hvordan nyanser og kompleksitet påvirker hvilke sikringstiltak som fungerer. Vi vil også lære hvordan den undergrunnsøkonomien i cyberverden fungerer, slik at du kan ta gode beslutninger for å beskytte din egen og din virksomhets informasjon.    Være i stand til å forklare hva cyberkriminalitet er, og hvorfor cybersikkerhet er viktig Være i stand til å forstå hvorfor cybersikkerhet er komplekst Være i stand til å analysere hvilke risikoer som du og din virksomhet står ovenfor Være i stand til å finne og beskytte din mest verdifulle informasjon Være i stand til å håndtere sikkerhetsbrudd på en betryggende måte Morgendagens trusler   Introduksjon til kurset Hvordan er det å bli hacket Hvem er hackerene? God cybersikkerhet – en forutsetning for vellykket digitalisering Hvordan ser cyberspace ut? Å jobbe strukturert med cybersikkerhet 4 myter om cybersikkerhet Personvern og cybersikkerhet Hva er risiko, og hvordan måler du den? Vurdere og redusere risiko – tips og triks Hvordan kommunisere med ledelsen om risiko? Digitalisering og tilpasning til din virksomhet Effektive sikkerhetstiltak for din virksomhet Effektive sikkerhetstiltak for deg som person Rammeverk og verktøy Fremtidige utfordringer Hjelp jeg har blitt hacket Hvem som kan hjelpe Oppsummering og videre læring [-]

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     [-]

Risikomomentene rundt kunstig intelligens er mange og berører flere fagområder. Hovedutfordringen med trygg og ansvarlig bruk av kunstig intelligens og maskinlæring er at problemstillingene utfordrer mange helt ulike fagområder, og tar opp mange temaer samfunnet aldri før har tatt stilling til. I dette kurset introduserer AI-ekspert Inga Strümke deg for de etiske, tekniske, juridiske og samfunnsmessige aspektene, og du vil få et helhetlig bilde av utfordringene og mulighetene. Fra før av har Inga Strümke laget kurset “En innføring i kunstig intelligens og maskinlæring” med Videocation. Vi anbefaler deg å se innføringskurset før du ser dette kurset om kunstig intelligens og risiko.  Introduksjon til kurset Innføring i AI-etikk Egne prosedyrer Falske nyheter og AI-skribenter Deepfakes Syntetiske data Angrep og mål Cybersikkerhet og IoT AI-regulering Personvern og differential privacy Rettferdighet Maskiner som tar jobbene og beslutningene våre Bærekraft Oppsummering [-]

GDPR - Certified Data Protection Officer [-]