Oversikt over relevante kurs innen IT-kurs i Torød

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 - 40 spørsmål skal besvares, og du består med 70% riktige svar (dvs. 28 av 40). Deltakerne har 1 time og 30 minutter til rådighet på eksamen.  Ingen hjelpemidler er tillatt.  Nødvendige forkunnskaper: Bestått ITIL Foundation sertifisering Gjennomført godkjent kurs/e-læring [-]

Kurset er rettet mot deg som vil lære grunnprinsippene og arbeidsmetodikk i Autodesk Revit og som jobber med byggeteknikk og armering.  I løpet av kurset gjøres øvelser for alle emner som blir tatt opp. Hensikten med kurset er at du skal få en grunnleggende forståelse i bruken av tegne- og konstruksjonsprogrammet Autodesk Revit. Kurset er nødvendig for å komme raskt i gang med bruk av programmet, og for å få den nødvendige forståelse for de mulighetene programmet gir. Du 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 Brukergrensesnitt Behandling av visninger Søyler Bjelker Dekker Vegger Utsparinger Editeringsverktøy Dimensjonering/Tekst Detaljering Utskrift [-]

Throughout four years of teaching my High-Performance Java Persistence course, I came to realize that there is so much Java developers can learn about the latest SQL features introduced by Oracle, SQL Server, PostgreSQL, or MySQL.This training spans over the course of 2 days and covers the Top 4 relational database systems: Oracle, SQL Server, PostgreSQL, and MySQL.From execution plans to the best way to paginate data, this training explains lesser-known techniques such as LATERAL JOIN, CROSS APPLY, as well as Derived Tables, Common Table Expressions, recursive queries, and the amazing Window Functions, PIVOT, or UPSERT statements.Last but not least, we are going to learn that, not only modern databases support JSON column types, but you can combine JSON structures with the traditional relational ones, therefore getting the best of both worlds.All examples are inspired by real-life scenarios, and they come in a GitHub repository for which attendees have exclusive and unlimited time access.At the end of these two days of training, the attendees will be better prepared to solve various data-intensive tasks using all these awesome SQL features that have been over the past 20 years.Agenda  Day 1Introduction - 1h 30m    - Beyond SQL:92    - SQL Parsing    - SQL Operation Order    - TOP-N queries    - OFFSET pagination    - Keyset PaginationSubqueries - 1h 15m    - EXISTS and NOT EXISTS    - IN and NOT IN    - ANY and ALL    - INSERT with subqueries    - Aggregation with subqueries   Joins - 1h 15m    - CROSS JOIN    - INNER and LEFT/RIGHT OUTER JOIN    - FULL OUTER JOIN    - NATURAL JOIN    - LATERAL JOIN and CROSS APPLYDay 2Window Functions - 1h 30m    - Analytics queries and window frame processing    - ROW_NUMBER, RANK, and DENSE_RANK    - FIRST_VALUE, LAST_VALUE, LEAD and LAG    - CUME_DIST and PERCENT_RANK    - PERCENTILE_DISC and PERCENTILE_CONTDerived Tables, CTE, Hierarchical Queries - 1h 30m    - Derived Tables    - CTE (Common Table Expressions)    - Recursive CTE    - Hierarchical queries   PIVOT, UNPIVOT, FILTER, and CASE - 1h    - CASE Expressions    - PostgreSQL FILTER Expressions    - PIVOT    - UNPIVOTDay 3UPSERT and MERGE - 30m- MERGE statements- UPSERT statements   JSON processing - 1h 30m    - Schemaless data structures and JSON    - JSON queries    - EAV Model   Transactions and Concurrency Control - 2h    - ACID, 2PL, MVCC    - Isolation Levels and anomalies    - Pessimistic and optimistic locking    - SKIP_LOCKED, NOWAIT [-]

AI-050: Develop Generative AI Solutions with Azure OpenAI Service [-]

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

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   [-]

I kurset ”Måling og mengdebereging” vil du lære hvordan Revu brukes til å kalibrere og måle på PDF-tegninger, samt hvordan du kan opprette, spare og dele tilpassede markeringsverktøy. Disse kan så brukes til effektiv beregning av mengder og priser på alt fra vegg- og gulvarealer, til prising av utstyr på en riggplan. Å lære å bruke Revu til måling og mengdeberegning vil bl.a. gi følgende fordeler: Stor tidsbesparelse Større nøyaktighet og mindre feil Bedre dokumentasjon av mengdeberegningen Oppnå optimal utnyttelse av Bluebeam Revu i prosjektene [-]

Kursinnhold Hva slags data kan brukes som grunnlag for et diagram Stolpediagram Sektordiagram Kombinert diagram Formatering av diagrammer Tips og triks Smarte løsninger Sparkline Hurtiganalyse Bruk av Excels diagrammer i andre Office-programmer [-]

COURSE OVERVIEW You’ll learn how to implement and secure a wireless network infrastructure and use Cisco Identity Service Engine (ISE), Cisco Prime Infrastructure (PI), and Cisco Connect Mobile Experience to monitor and troubleshoot network issues.   The course provides hands-on labs to reinforce concepts including deploying Cisco Prime Infrastructure Release 3.5, Cisco Catalyst 9800 Wireless Controller Release IOS XE Gibraltar 16.10, Cisco Digital Network Architecture (DNA) Center Release 1.2.8, Cisco CMX Release 10.5, Cisco MSE Release 8.0 features and Cisco Identity Services Engine (ISE) Release 2.4.   This course also helps you prepare to take the Implementing Cisco Enterprise Wireless Networks (300-430 ENWLSI) exam, which is part of the new CCNP Enterprise certification. Passing the exam will also provide you with the Cisco Certified Specialist - Enterprise Wireless Implementation certification.   TARGET AUDIENCE Individuals needing to understand how to implement, secure and troubleshoot a Cisco Enterprise Wireless Network.   COURSE OBJECTIVES After completing this course you should be able to: Implement network settings to provide a secure wireless network infrastructure Troubleshoot security issues as it relates to the wireless network infrastructure Implement a secure wireless client and troubleshoot wireless client connectivity issues Implement and troubleshoot QoS in wireless networks Implement and troubleshoot advanced capabilities in wireless network services   COURSE CONTENT Securing and Troubleshooting the Wireless Network Infrastructure Implement Secure Access to the WLCs and Access Points Configure the Network for Access Point 802.1X Authentication Use Cisco DNA Center for Controller and AP Auto Install Implement Cisco Prime Infrastructure Define Network Troubleshooting Techniques Troubleshoot Access Point Join Issues Monitor the Wireless Network Implementing and Troubleshooting Secure Client Connectivity Configure the Cisco WLC for Wireless Client 802.1x Authentication Configure the Wireless Client for 802.1X Authentication Configure a Wireless LAN for FlexConnect Implement Guest Services in the Wireless Network Configure the Cisco WLC for Centralized Web Authentication Configure Central Web Authentication on Cisco ISE Implement BYOD Implement Location-Aware Guest Services Troubleshoot Client Connectivity Describe Issues that Affect Client Performance Monitor Wireless Clients Implementing and Troubleshooting QoS in Wireless Networks Implement QoS in the Wireless Network Configure the Cisco WLC to Support Voice Traffic Optimize Wireless Utilization on the Cisco WLC Implement Cisco AVC in the Wireless Network Implement Multicast Services Implement mDNS Service Implement Cisco Media Stream Troubleshoot QoS Issues in the Wireless Network Troublehoot mDNS Issues Troubleshoot Media Stream Issues Implementing and Troubleshooting Advanced Wireless Network Services Implement Base Location Services on Cisco Prime Infrastructure Implement Hyperlocation in the Wireless Network Implement Detect and Locate Services on Cisco CMX Implement Analytics on Cisco CMX Implement Presence Services on Cisco CMX Monitor and Locate Rogue Devices with Cisco Prime Infrastructure and Cisco CMX Monitor and Detect Wireless Clients with Cisco CMX and Cisco DNA Center Run Analytics on Wireless Clients Troubleshoot Location Accuracy with Cisco Hyperlocation Monitor and Manage RF Interferers on the Cisco WLC Monitor and Manager RF Interferers on Cisco Prime Infrastructure and Cisco CMX Labs Lab Familiarization (Base Learning Lab) Configure Secure Management Access for WLCs and APs Add Network Devices and External Resources to Cisco Prime Infrastructure Capture a Successful AP Authentication Implement AAA Services for Central Mode WLANs Implement AAA Services for FlexConnect Mode WLANs Configure Guest Services in the Wireless Network Configure BYOD in the Wireless Network Capture a Successful Client Authentications Configure QoS in the Wireless Network for Voice and Video Services Configure Cisco AVC in the Wireless Network Capture Successful QoS Traffic Marking in the Wireless Network Configure Detect and Locate Services on the Cisco CMX Identify Wireless Clients and Security Threats [-]

Bli kjent med Revu (Bruksområder, grensesnitt, menyer, verktøy, paneler og profiler) Grunnleggende PDF-håndtering med Revu Markeringsverktøy og måleverktøy Innføring i Tool Chest Innføring i Markeringslisten Innføring i Studio [-]

Her er et utvalg av temaene du vil lære på kurset: Oppsett av nytt sprinklerprosjekt i Revit Prosjektering av sprinkleranlegg Behandling av rørtyper, systemer etc Lage egne produkter for sprinklerhoder og andre produkter Hydrauliske beregninger IFC-eksport Oppsett av tegninger [-]

ITIL® 4 Specialist: Monitor, Support and Fulfil [-]

CCNA: Implementing and Administering Cisco Solutions [-]

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. After completing this course, students will be able to: 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 prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.Recommended prerequisites:M-DP900 - Microsoft Azure Data FundamentalsM-AZ900 - Microsoft Azure Fundamentals Agenda 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. 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. 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. 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). 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Module 16: Build reports using Power BI integration with Azure Synapase 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. 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. [-]

Introduksjon Kurset gir deg en grunnleggende innføring i ITIL® beste praksis rammeverket versjon 4. Kurset gir innføring i basis konseptet, prinsippene, prosessene og funksjonene som er definert som beste praksis. Kurset vil også forberede deg til å gjennomføre ITIL Foundation sertifiseringtest. ForutsetningerIngen forutsetninger for å delta på kurset.Faglige kvalifikasjonKurset leder frem til ITIL Foundation Certificate.(Sertifiseringstest gjennomføres på siste kursdag)KursdokumentasjonOmfattende kursdokumentasjon som inneholder Kurskompendium, ITIL Pocket Guide, Norsk-Engelsk ordliste, 115 testoppgaver.SertifiseringInkludert i kursprisen er ITIL Fondation eksamen EXIN.Eksamen gjennomføres på ettermiddagen dag 3 - den avholdes skriftlig og er på engelsk.Eksamensformen er multiple choice - 40 spørsmål skal besvares, og du består ved 65% korrekte svar (dvs 26 av 40 spørsmål). Deltakerne har 1 time og 15 minutter til rådighet på eksamen. ITIL® is a registered trade mark of AXELOS Limited.   Kursinnhold Service Management as a practise • Innføring i IT Service Management• BESTE PRAKSIS: Forstå hva og hvorfor• Tjenesteorientering The Service Lifecycle Innføring i alle fasene av livssyklusen - målene og forretningsverdien for hver fase.• Service Strategy• Service Design• Service Transition• Service Operations• Continual Service Improvement Service Management processes Hvordan de ulike prosessene spiller inn i livssyklusen. Vi diskuterer mål, omfang, aktiviteter, nøkkeltall og annet: Service Strategy • Strategy Management• Service Portfolio Management• Demand Management• Financial Management Service Design • Design Coordination• Service Catalogue Management• Service Level Management• Supplier Management• Availability Management• Capacity Management• IT Service Continuity Management• Information Security Management Service Transition • Transition planning and support• Change Management• Service Asset and Configuration Management• Release and Deployment Management Service Operations • Event Management• Incident Management• Request Fulfilment• Problem Management Continual Service Operations • Continual Service Improvement model• The seven-step improvement process Continual Service Operations • Continual Service Improvement model• The seven-step improvement process Functions Forstå mål, organisasjonsstruktur, bemanning, nøkkeltall og sammenhenger i ulike funksjoner• Service Desk• Technical Management• Application Management• IT Operations Management (IT Operations Control, Facilities Management) Roles Ansvar og funksjon hos de to nøkkelrollene i Service Management og innblikk i øvrige roller.• RACI modell• Process owner• Service owner Technology and Architecture • Service Management Technology [-]