Kurs i programvare og applikasjoner

PowerPoint 2010 er et presentasjonsprogram som brukes når vi skal vise fram data – enten det er tekst, bilder, tall eller tegninger. Programmet kan brukes til å lage lysark som skrives ut, eller vi kan vise presentasjonen ved hjelp av PC + videokanon. På kurset vil grunnleggende funksjoner vektlegges, men vi vil og se på hvordan en bygger opp og setter sammen en presentasjon. Forkunnskaper: Du må ha kunnskaper tilsvarende PC-begynnerkurs. Brukere av Powerpoint 2007 kan og følge dette kurset. [-]

Du vil få tilsendt en «Core guidance» bok og sertifiserings-voucher i en e-post fra Peoplecert. 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.     [-]

Develop dynamic reports with Microsoft Power BI [-]

Ønsker du å lære hvordan du lager forskjellige Word maler og utformer brukervennlige grensesnitt? Vil du i tillegg vite hvordan du lager dialogbokser som brukeren kan fylle ut slik at dataene blir plassert på riktig sted i dokumentet? Da er ”Dokumentmaler i Word med Visual Basic” kurset for deg! Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1   Enkle maler Begreper. Forstå forskjellen på mal og dokument. Topp- og bunntekst. Hvordan sørge for at kun forsiden har logo og ikke eventuelle påfølgende sider? Skjemamaler. Lær å bruke skjemafelter for å sikre at annen tekst i dokumentet er låst. Navigering. Hvordan lage maler som gjør det enkelt for brukeren å navigere til riktig sted? Introduksjon til Visual Basic (VBA) Dato. Lær å sette inn dagens dato på en sikker måte. Bokmerker. Få kunnskap om hva bokmerker er og hvordan disse brukes i malsammenheng Prinsipper for VBA. Lær om variabler, IF-setninger, meldingsbokser og løkker Oppstart av mal. Lær hvordan du kan lage automatikk knyttet til oppstart av en mal, som for eksempel innsetting av dagens dato, navn og initialer.   Dag 2   Egendefinert dialogboks Design. Lær hvordan du designer en dialogboks med tekstbokser, kombinasjonsbokser og knapper. Oppstart. Få kunnskap om hvordan dialogbokser kan gjøres tilgjengelig for malbrukeren   Feilsøking Finne feil. Lær om feilsøkingsmuligheter i VBA for å rette opp kode.   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

Objectives This course teaches participants the following skills: Design and build data processing systems on Google Cloud Platform Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow Derive business insights from extremely large datasets using Google BigQuery Train, evaluate, and predict using machine learning models using Tensorflow and Cloud ML Leverage unstructured data using Spark and ML APIs on Cloud Dataproc Enable instant insights from streaming data   All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introduction to Data Engineering -Explore the role of a data engineer-Analyze data engineering challenges-Intro to BigQuery-Data Lakes and Data Warehouses-Demo: Federated Queries with BigQuery-Transactional Databases vs Data Warehouses-Website Demo: Finding PII in your dataset with DLP API-Partner effectively with other data teams-Manage data access and governance-Build production-ready pipelines-Review GCP customer case study-Lab: Analyzing Data with BigQuery Module 2: Building a Data Lake -Introduction to Data Lakes-Data Storage and ETL options on GCP-Building a Data Lake using Cloud Storage-Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions-Securing Cloud Storage-Storing All Sorts of Data Types-Video Demo: Running federated queries on Parquet and ORC files in BigQuery-Cloud SQL as a relational Data Lake-Lab: Loading Taxi Data into Cloud SQL Module 3: Building a Data Warehouse -The modern data warehouse-Intro to BigQuery-Demo: Query TB+ of data in seconds-Getting Started-Loading Data-Video Demo: Querying Cloud SQL from BigQuery-Lab: Loading Data into BigQuery-Exploring Schemas-Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA-Schema Design-Nested and Repeated Fields-Demo: Nested and repeated fields in BigQuery-Lab: Working with JSON and Array data in BigQuery-Optimizing with Partitioning and Clustering-Demo: Partitioned and Clustered Tables in BigQuery-Preview: Transforming Batch and Streaming Data Module 4: Introduction to Building Batch Data Pipelines -EL, ELT, ETL-Quality considerations-How to carry out operations in BigQuery-Demo: ELT to improve data quality in BigQuery-Shortcomings-ETL to solve data quality issues Module 5: Executing Spark on Cloud Dataproc -The Hadoop ecosystem-Running Hadoop on Cloud Dataproc-GCS instead of HDFS-Optimizing Dataproc-Lab: Running Apache Spark jobs on Cloud Dataproc Module 6: Serverless Data Processing with Cloud Dataflow -Cloud Dataflow-Why customers value Dataflow-Dataflow Pipelines-Lab: A Simple Dataflow Pipeline (Python/Java)-Lab: MapReduce in Dataflow (Python/Java)-Lab: Side Inputs (Python/Java)-Dataflow Templates-Dataflow SQL Module 7: Manage Data Pipelines with Cloud Data Fusion and Cloud Composer -Building Batch Data Pipelines visually with Cloud Data Fusion-Components-UI Overview-Building a Pipeline-Exploring Data using Wrangler-Lab: Building and executing a pipeline graph in Cloud Data Fusion-Orchestrating work between GCP services with Cloud Composer-Apache Airflow Environment-DAGs and Operators-Workflow Scheduling-Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, -Cloud Storage, and BigQuery-Monitoring and Logging-Lab: An Introduction to Cloud Composer Module 8: Introduction to Processing Streaming Data Processing Streaming Data Module 9: Serverless Messaging with Cloud Pub/Sub -Cloud Pub/Sub-Lab: Publish Streaming Data into Pub/Sub Module 10: Cloud Dataflow Streaming Features -Cloud Dataflow Streaming Features-Lab: Streaming Data Pipelines Module 11: High-Throughput BigQuery and Bigtable Streaming Features -BigQuery Streaming Features-Lab: Streaming Analytics and Dashboards-Cloud Bigtable-Lab: Streaming Data Pipelines into Bigtable Module 12: Advanced BigQuery Functionality and Performance -Analytic Window Functions-Using With Clauses-GIS Functions-Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz-Performance Considerations-Lab: Optimizing your BigQuery Queries for Performance-Optional Lab: Creating Date-Partitioned Tables in BigQuery Module 13: Introduction to Analytics and AI -What is AI?-From Ad-hoc Data Analysis to Data Driven Decisions-Options for ML models on GCP Module 14: Prebuilt ML model APIs for Unstructured Data -Unstructured Data is Hard-ML APIs for Enriching Data-Lab: Using the Natural Language API to Classify Unstructured Text Module 15: Big Data Analytics with Cloud AI Platform Notebooks -What’s a Notebook-BigQuery Magic and Ties to Pandas-Lab: BigQuery in Jupyter Labs on AI Platform Module 16: Production ML Pipelines with Kubeflow -Ways to do ML on GCP-Kubeflow-AI Hub-Lab: Running AI models on Kubeflow Module 17: Custom Model building with SQL in BigQuery ML -BigQuery ML for Quick Model Building-Demo: Train a model with BigQuery ML to predict NYC taxi fares-Supported Models-Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML-Lab Option 2: Movie Recommendations in BigQuery ML Module 18: Custom Model building with Cloud AutoML -Why Auto ML?-Auto ML Vision-Auto ML NLP-Auto ML Tables [-]

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. [-]

COURSE OVERVIEW In this course, you will master the skills and technologies you need to implement core Cisco security solutions to provide advanced threat protection against cybersecurity attacks. You will learn security for networks, cloud and content, endpoint protection, secure network access, visibility and enforcements. You will get extensive hands-on experience deploying Cisco Firepower Next-Generation Firewall and Cisco ASA Firewall; configuring access control policies, mail policies, and 802.1X Authentication; and more.  You will get introductory practice on Cisco Stealthwatch Enterprise and Cisco Stealthwatch Cloud threat detection features. Please note that this course is a combination of Instructor-Led and Self-Paced Study - 5 days in the classroom and approx 3 days of self study. The self-study content will be provided as part of the digital courseware that you will recieve at the beginning of the course and should be part of your preparation for the exam. TARGET AUDIENCE Security individuals who need to be able to implement and operate core security technologies including network security, cloud security, content security, endpoint protection and detection, secure network access, visibility and enforcements. COURSE OBJECTIVES After completing this course you should be able to: Describe information security concepts and strategies within the network Describe common TCP/IP, network application, and endpoint attacks Describe how various network security technologies work together to guard against attacks Implement access control on Cisco ASA appliance and Cisco Firepower Next-Generation Firewall Describe and implement basic email content security features and functions provided by Cisco Email Security Appliance Describe and implement web content security features and functions provided by Cisco Web Security Appliance Describe Cisco Umbrella security capabilities, deployment models, policy management, and Investigate console Introduce VPNs and describe cryptography solutions and algorithms Describe Cisco secure site-to-site connectivity solutions and explain how to deploy Cisco IOS VTI-based point-to-point IPsec VPNs, and point-to-point IPsec VPN on the Cisco ASA and Cisco FirePower NGFW Describe and deploy Cisco secure remote access connectivity solutions and describe how to configure 802.1X and EAP authentication Provide basic understanding of endpoint security and describe AMP for Endpoints architecture and basic features Examine various defenses on Cisco devices that protect the control and management plane Configure and verify Cisco IOS Software Layer 2 and Layer 3 Data Plane Controls Describe Cisco Stealthwatch Enterprise and Stealthwatch Cloud solutions Describe basics of cloud computing and common cloud attacks and how to secure cloud environment   COURSE CONTENT Describing Information Security Concepts (Self-Study) Information Security Overview Managing Risk Vulnerability Assessment Understanding CVSS Describing Common TCP/IP Attacks (Self-Study) Legacy TCP/IP Vulnerabilities IP Vulnerabilities ICMP Vulnerabilities TCP Vulnerabilities UDP Vulnerabilities Attack Surface and Attack Vectors Reconnaissance Attacks Access Attacks Man-In-The-Middle Attacks Denial of Service and Distributed Denial of Service Attacks Reflection and Amplification Attacks Spoofing Attacks DHCP Attacks Describing Common Network Application Attacks (Self-Study) Password Attacks DNS-Based Attacks DNS Tunneling Web-Based Attacks HTTP 302 Cushioning Command Injections SQL Injections Cross-Site Scripting and Request Forgery Email-Based Attacks Describing Common Endpoint Attacks (Self-Study) Buffer Overflow Malware Reconnaissance Attack Gaining Access and Control Gaining Access via Social Engineering Gaining Access via Web-Based Attacks Exploit Kits and Rootkits Privilege Escalation Post-Exploitation Phase Angler Exploit Kit Describing Network Security Technologies Defense-in-Depth Strategy Defending Across the Attack Continuum Network Segmentation and Virtualization Overview Stateful Firewall Overview Security Intelligence Overview Threat Information Standardization Network-Based Malware Protection Overview IPS Overview Next Generation Firewall Overview Email Content Security Overview Web Content Security Overview Threat Analytic Systems Overview DNS Security Overview Authentication, Authorization, and Accounting Overview Identity and Access Management Overview Virtual Private Network Technology Overview Network Security Device Form Factors Overview Deploying Cisco ASA Firewall Cisco ASA Deployment Types Cisco ASA Interface Security Levels Cisco ASA Objects and Object Groups Network Address Translation Cisco ASA Interface ACLs Cisco ASA Global ACLs Cisco ASA Advanced Access Policies Cisco ASA High Availability Overview Deploying Cisco Firepower Next-Generation Firewall Cisco Firepower NGFW Deployments Cisco Firepower NGFW Packet Processing and Policies Cisco Firepower NGFW Objects Cisco Firepower NGFW NAT Cisco Firepower NGFW Prefilter Policies Cisco Firepower NGFW Access Control Policies Cisco Firepower NGFW Security Intelligence Cisco Firepower NGFW Discovery Policies Cisco Firepower NGFW IPS Policies Cisco Firepower NGFW Malware and File Policies Deploying Email Content Security Cisco Email Content Security Overview SMTP Overview Email Pipeline Overview Public and Private Listeners Host Access Table Overview Recipient Access Table Overview Mail Policies Overview Protection Against Spam and Graymail Anti-virus and Anti-malware Protection Outbreak Filters Content Filters Data Loss Prevention Email Encryption Deploying Web Content Security Cisco WSA Overview Deployment Options Network Users Authentication HTTPS Traffic Decryption Access Policies and Identification Profiles Acceptable Use Controls Settings Anti-Malware Protection Deploying Cisco Umbrella (Self-Study) Cisco Umbrella Architecture Deploying Cisco Umbrella Cisco Umbrella Roaming Client Managing Cisco Umbrella Cisco Umbrella Investigate Overview Explaining VPN Technologies and Cryptography VPN Definition VPN Types Secure Communication and Cryptographic Services Keys in Cryptography Public Key Infrastructure Introducing Cisco Secure Site-to-Site VPN Solutions Site-to-Site VPN Topologies IPsec VPN Overview IPsec Static Crypto Maps IPsec Static Virtual Tunnel Interface Dynamic Multipoint VPN Cisco IOS FlexVPN Deploying Cisco IOS VTI-Based Point-to-Point Cisco IOS VTIs Static VTI Point-to-Point IPsec IKEv2 VPN Configuration Deploying Point-to-Point IPsec VPNs on the Cisco ASA and Cisco Firepower NGFW Point-to-Point VPNs on the Cisco ASA and Cisco Firepower NGFW Cisco ASA Point-to-Point VPN Configuration Cisco Firepower NGFW Point-to-Point VPN Configuration Introducing Cisco Secure Remote Access VPN Solutions Remote Access VPN Components Remote Access VPN Technologies SSL Overview Deploying Remote Access SSL VPNs on the Cisco ASA and Cisco Firepower NGFW Remote Access Configuration Concepts Connection Profiles Group Policies Cisco ASA Remote Access VPN Configuration Cisco Firepower NGFW Remote Access VPN Configuration Explaining Cisco Secure Network Access Solutions Cisco Secure Network Access Cisco Secure Network Access Components AAA Role in Cisco Secure Network Access Solution Cisco Identity Services Engine Cisco TrustSec Describing 802.1X Authentication 802.1X and EAP EAP Methods Role of RADIUS in 802.1X Communications RADIUS Change of Authorization Configuring 802.1X Authentication Cisco Catalyst Switch 802.1X Configuration Cisco WLC 802.1X Configuration Cisco ISE 802.1X Configuration Supplicant 802.1x Configuration Cisco Central Web Authentication Describing Endpoint Security Technologies (Self-Study) Host-Based Personal Firewall Host-Based Anti-Virus Host-Based Intrusion Prevention System Application Whitelists and Blacklists Host-Based Malware Protection Sandboxing Overview File Integrity Checking Deploying Cisco AMP for Endpoints (Self-study) Cisco AMP for Endpoints Architecture Cisco AMP for Endpoints Engines Retrospective Security with Cisco AMP Cisco AMP Device and File Trajectory Managing Cisco AMP for Endpoints Introducing Network Infrastructure Protection (Self-Study) Identifying Network Device Planes Control Plane Security Controls Management Plane Security Controls Network Telemetry Layer 2 Data Plane Security Controls Layer 3 Data Plane Security Controls Deploying Control Plane Security Controls (Self-Study) Infrastructure ACLs Control Plane Policing Control Plane Protection Routing Protocol Security Deploying Layer 2 Data Plane Security Controls (Self-Study) Overview of Layer 2 Data Plane Security Controls VLAN-Based Attacks Mitigation STP Attacks Mitigation Port Security Private VLANs DHCP Snooping ARP Inspection Storm Control MACsec Encryption Deploying Layer 3 Data Plane Security Controls (Self-Study) Infrastructure Antispoofing ACLs Unicast Reverse Path Forwarding IP Source Guard Labs Configure Network Settings And NAT On Cisco ASA Configure Cisco ASA Access Control Policies Configure Cisco Firepower NGFW NAT Configure Cisco Firepower NGFW Access Control Policy Configure Cisco Firepower NGFW Discovery and IPS Policy Configure Cisco NGFW Malware and File Policy Configure Listener, HAT, and RAT on Cisco ESA Configure Mail Policies Configure Proxy Services, Authentication, and HTTPS Decryption Enforce Acceptable Use Control and Malware Protection Examine the Umbrella Dashboard Examine Cisco Umbrella Investigate Explore DNS Ransomware Protection by Cisco Umbrella Configure Static VTI Point-to-Point IPsec IKEv2 Tunnel Configure Point-to-Point VPN between the Cisco ASA and Cisco Firepower NGFW Configure Remote Access VPN on the Cisco Firepower NGFW Explore Cisco AMP for Endpoints Perform Endpoint Analysis Using AMP for Endpoints Console Explore File Ransomware Protection by Cisco AMP for Endpoints Console Explore Cisco Stealthwatch Enterprise v6.9.3 Explore CTA in Stealthwatch Enterprise v7.0 Explore the Cisco Cloudlock Dashboard and User Security Explore Cisco Cloudlock Application and Data Security Explore Cisco Stealthwatch Cloud Explore Stealthwatch Cloud Alert Settings, Watchlists, and Sensors TEST CERTIFICATION Recommended as preparation for the following exams: 350-701 - Implementing and Operating Cisco Security Core Technologies (SCOR 350-701)   This is the core exam for the Cisco CCNP Security certification, in order to gain the CCNP Security certification you will also need to pass one of the concentration exams. 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Kubernetes Administration (LFS458) [-]

AZ-900: Microsoft Azure Fundamentals [-]

ICONS holder grunnkurs, videregående og spesialkurs i Adobe InDesign. Kursene holdes ofte som privatkurs for én person eller for et par personer med samme interesser. NOK 2000 for én dag og NOK 1800 for eventuelle etterfølgende dager. Norsk kurs-kompendium på 50 sider+ følger med alle kurs og har step-by-step oppskrifter og oppgaver.    Adobe InDesign er det mest populære DeskTop Publishing program på markedet. InDesign brukes til produksjon av reklame, tidsskrifter, ukeblader, kataloger, brosyrer, aviser, bøker, bannere, e-læring, nettbrett, smarttelefoner.... InDesign på CV'en kan være bra!   Verktøy og menyer i InDesign Tekst, bilder, figurer, farger... Stiler, sidemaler og dokumentmaler Vi lager postkort, tidsskrift/hefte, plakat... Konvertering til PDF for web og trykk Alle kurs er praktisk rettet med "hands-on" gjennom hele kursdagen.   Videregående kurs mest populært for utdypning, men dessuten bokproduksjon, inkludering av film, lyd, video, design for nettbrett...   Kursleder Elisabeth Buntz har erfaring med InDesign fra 1999 - ...   [-]

Kurset passer for deg som allerede vet hvordan du skal lage enkle presentasjoner i PowerPoint, men som ønsker å gå et trinn videre. Vi vil gi deg gode tips om hvordan du kan lage bedre presentasjoner, og jobbe mer effektivt med å lage lysbilder som engasjerer publikum og får frem budskapet. Mål for kursetEtter endt kurs skal du kunne bruke verktøyet på en smart og effektiv måte. Varighet1 dag fra 09:00 til 15:00 ForkunnskaperNoe kjennskap til PowerPoint. MålgruppeDette kurset er for deg som vet litt om PowerPoint og som ønsker å lære effektiv bruk av verktøyet. UndervisningsformKlasseromsundervisning med maks 12 deltakere. En maskin utlånt til hver deltaker. Pris3900 kroner inkludert lunsj og kursdokumentasjon. Ansatte ved UiS har egne betingelser på dette kurset. Emner Merketeknikker Navigering og snarveger Lage ny presentasjon raskt og enkelt Enkel og praktisk presentasjonsteknikk Disposisjonsvisning Maler Plassholdere Gjenbruk av lysbilder Tekst fra Word Fargevalg Konverter punkter til SmartArt Skrifttyper Hurtigstiler Effekter på bilder, figurer og Smart Art Bildebehandling Tegn figurer Rutenett og støttelinjer Juster og fordel objekter Video fra fil Legg til en tabell, formater og bruk Sett opp organisasjonskart Legg til et diagram, formater og bruk Hent diagram fra Excel Animering av punkter, bilder og figurer Egendefinert lysbildefremvisning Pakk til USB – vis uansett hvor Send som .pdf på e-post Utskrift av støtteark [-]

Trenger du å bygge opp store og avanserte regneark? Ønsker du å lage rapporter og beregninger på store tallgrunnlag? Vil du finne ut hvordan du kan effektivisere arbeidet ditt i Excel? Ønsker du å lære de første stegene mot automatiserte rapporter? Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1    Generelt om regneark Om regneark og infrastruktur Bruke tastatur og hurtigtaster effektiv Absolutte referanser og definerte navn   Funksjoner Mer om funksjoner, hvis, antall.hvis, summer.hvis.sett Lær om "må ha funksjonen" Finn.rad [Vlookup] Andre funksjoner for spesielle oppgaver   Avansert formatering Spesiell formatering – dato, tekst og egendefinert Betinget formatering og cellestiler   Dag 2    Lister og tabeller Viktige regler og råd Bruk av autofilter og sortering Tabellfunksjonalitet Validering ved inntasting Beregninger av store datamengder via gode funksjoner   Pivottabell Hva er pivottabell og hvordan lage raske og enkle rapporter Utvidede muligheter i Pivot som grupperinger, vis verdier som og slicer   Dag 3   Metoder for dataimport Direkte import fra database   Innføring til makro Spille inn /registrere makro Ord/uttrykk og VBA editor   Datavask Slette tommer rader, fylle tomme celler Bruk av funksjoner for å klargjøre datagrunnlag Identifisere og håndtere avvik i grunnlag   Alternative temaer (hvis tid) Tips til diagrammer Hva hvis analyse Konsolidering   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

Vil du jobbe mer effektivt med logoer, figurer, farger og lag? Vil du lære deg mer om verdens beste og mest solide tegneprogram? Da er ”Adobe Illustrator Grunnleggende” kurset for deg! Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold   Arbeidsmiljø Vektorgrafikk og punktgrafikk. Hva er forskjellen? Vi ser på fordeler og ulemper med formatene Menyer og paletter. Hva inneholder disse, og hvordan får du fram det du ønsker? Tilpasse arbeidsmiljøet. Flytte på paletter og lagre egne oppsett tilpasset dine behov Ord og uttrykk. Forklaring av vanlige begreper brukt i programmet, på Internett og hos trykkerier Skape og forme figurer og logoer Lage former. Alt fra sirkler og rektangler til helt egendefinerte former Størrelse og form. Tilpasse størrelse og form på figurer Lage logo. Kombinere tekst og figurer og litt tips til logooppbygning\nGruppering. Slå sammen og løse opp figurer i gruppe Fritegning. Jobbe kreativt og produktivt med blyantverktøy Symboler. Lage faste elementer som symboler for å spare tid og jobbe smartere Farger, fyll og strek Fyllfarger. Legge fyllfarger med og uten effekter i figurer Strekfarger. Legge farge, tykkelse og stil på streker og linjer rundt figurer Pensler. Få oversikt over de forskjellige penslene og kontroll på hvordan de kan benyttes. Farger, fyll og strek Fargeprøver. Definere og lagre farger du skal bruke mye og gjøre de lett tilgjengelige Mønstre. Slå sammen former til flotte mønstre som kan heve utseendet på dokumentet Gradering. Få full kontroll på mulighetene med graderinger Annet Lære og løse opp og jobbe med Illustrator filer som er skapt av andre Bildeformat. Litt om de vanligste formatene, størrelse og oppløsning Kreative tekstmuligheter. Vi ser på triks og verktøy som gir deg uante muligheter med tekst Vektorisere bilder. Gjøre om bilder eller logoer til vektorgrafikk Importere tekst. Hvor henter du teksten fra, og hvordan styrer du hvordan teksten skal importeres i Illustrator?   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

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     [-]

Kursinnhold JavaScript er nå det eneste skript-språket som anvendes og støttes av alle nettlesere og er blitt en defacto standard for å bygge inn interaktivitet på websider. AJAX, jQuery, Mootools, Node.js, Angular.js osv. bygger alle på JavaScript, og en grunnforståelse av hvordan dette språket virker er blitt essensielt for en webutvikler eller webansvarlig.     Målsetting Etter gjennomført grunnkurs skal deltakerne være fortrolige med JavaScripts grunnstruktur og funksjoner og skal kunne bruke JavaScript til å utvikle interaktive websider.   Kursinnhold Introduksjon til JavaScript og dets anvendelsesområder JavaScripts grunnleggende grammatikk JavaScripts innebygde funksjoner JavaScripts datatyper og variabler JavaScript og Dokumentobjektmodellen (DOM) JavaScripts kontrollstrukturer og betingelseslogikk Introduksjon til AJAX og kommunikasjon mellom klient og server Kort introduksjon til jQuery som AJAX-bibliotek   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 hands-on øvelsesoppgaver til hovedtemaene som gjennomgås.   [-]