Kurs i Askvoll

Modulen dekker bruk og effekt av Lean og agile arbeidsmåter, og hvordan dette kan utnyttes til fordel for organisasjonen. Kurset vil gi kandidatene en praktisk og strategisk metode for å planlegge og levere kontinuerlig forbedring med nødvendig smidighet.  E-læringskurset inneholder 18 timer med undervisning, og er delt inn i 12 moduler. Les mer om ITIL® 4 på AXELOS sine websider Du vil motta en e-post med tilgang til e-læringen, sertifiseringsvoucher og digital bok fra Peoplecert. Du avtaler tid for sertifiseringen som beskrevet i e-posten fra Peoplecert.   [-]

AZ-1008: Administer Active Directory Domain Services [-]

Spesialseminar 2: «Generasjonsskifter - utfordringer og løsninger»    Dette spesialseminaret er åpent og kostnadsfritt for alle som er med i styrenettverksgrupper arrangert av Styreforeningen. For andre deltakere som er medlemmer av Styreforeningen koster seminaret kr. 4.990,-.For deltakere som ikke er med i styrenettverksgrupper og som ikke er medlemmer av Styreforeningen er prisen kr. 5.990,-   Seminaret tar for seg en rekke krevende faser og situasjoner som kan oppstå i forbindelse med styrearbeidet. Vi ser blant annet på:   hva undersøkeler som er gjort omkring generasjonsskifteprosesser forteller oss uventet aksjonær bortgang og ulike utfordringer det kan medføre fremtidsfullmakt i forbindelse med aksjeeierskap og aksjeovertakels viktigheten av vedtektsbestemmelser eventuelt aksjonæravtaler ved generasjonsskifter, og utfordringene som kan oppstå dersom situasjonen ikke er hensynttat i formalia styrets rolle i generasjonsskifteprosesser forberedelsene og tilretteleggingen i generasjonsskifteprosesser sjekkliste ved generasjonsskifteprosesser [-]

Understand the purpose and key concepts of the Service Desk practice, including how it serves as the central point of contact between the service provider and the users, facilitating effective communication. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content mobil-optimised practical exercises     Exam: 20 questions Multiple Choice 30 minutes Closed book Minimum required score to pass: (65%)   [-]

I Matematikk R2 lærer du om integralregning, rekker, vektorer og trigonometri. Matematikk R2 er for deg som trenger realfagmatematikk for videre studier eller for å forbedre karakteren din. Faget er obligatorisk om du skal studere til ingeniør eller arkitekt. Matematikk R2 gir 1 realfagpoeng. Du må ha matematikk R1 for å ta dette faget. Gjennomføring NettstudierDu bestemmer hvor og når du vil lære. Her får du varierte leksjoner i form av tekster, video, quiz, podcast, veiledning og oppgaver. Du har alltid kontakt med din personlige lærer hos K2. Målet er å gjøre deg best mulig forberedt til eksamen. Eksamen Eksamen i Matematikk R2 er skriftlig. Som privatist må du selv melde deg opp til eksamen. Oppmeldingsfristene er normalt 15. september og 1. februar. Husk at betaling av eksamensavgiften skjer ved oppmelding. Veien videre Om du har generell studiekompetanse (GENS) og velger å ta fagene fysikk 1 og matematikk R1 og R2 som privatist, da oppfyller du opptakskravene til flere studier, inkludert ingeniørstudier. Se praktisk info for frister og opptak til universitet og høyskole. Gratis veiledning Er du usikker på hva som skal til for å få studiekompetanse, ta gjerne kontakt med oss for gratis veiledning. Vi har veiledere med mange års erfaring som står klare til å hjelpe deg!Ønsker du mer informasjon om kurset velg "Send meg info"-knappen under. Vil du chatte med oss, så klikk på ikonet nederst i høyre hjørne. Gratis veiledning Vi har veiledere med mange års erfaring som står klare til å hjelpe deg! Er du usikker på hva som skal til for å få studiekompetanse, ta gjerne kontakt med oss for gratis veiledning.  Ønsker du mer informasjon om kurset velg "Send meg info"-knappen under. Vil du chatte med oss, klikk på ikonet nederst i høyre hjørne. Lånekassestøtte Utdanningen er godkjent i lånekassen. Du søker direkte via lanekassen.no. Alt du må vite om lån og stipend fra Lånekassen som deltaker hos K2 utdanning Støtteordning Er du organisert i en fagforening, kan du i de fleste fagforeningene søke støtte til utdanning. Dersom du er organisert bør du sjekke med din fagforening om muligheter for støtte, frister og hvordan du søker. Forkunnskaper Du må ha fullført grunnskole eller tilsvarende opplæring. Minoritetsspråklige bør ha minimum B1-nivå i norsk muntlig og skriftlig. Dersom du har behov for å lære mere norsk før du starter på utdanning har vi norskkurs på forskjellig nivå (A1-B2). Språkkursene er digitale med personlig oppfølging fra lærer. Se alle norskkurs K2 tilbyr. Krav til utstyr Som deltaker hos K2 må du ha tilgang til pc på eksamen. I tillegg trenger du PC-versjonen av Office eller tilsvarende programmer. Se hva du har tilgang til av nettbaserte ressurser på eksamen. Praktisk info Du finner svar på ofte stilte spørsmål på nettsiden vår under praktisk info.     [-]

ITIL® Specialist - Drive Stakeholder Value [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: IINI1003 Databaser eller tilsvarende forhåndskunnskaper Innleveringer: Tilsvarende 8 obligatoriske øvinger må være godkjent før endelig karakter settes. Personlig veileder: ja Vurderingsform: Individuell netteksamen, 2 timer. Ansvarlig: Tore Mallaug Eksamensdato: 13.12.13 / 16.05.14         Læremål: KUNNSKAPERKandidaten:- kjenner sentrale begreper innen flerbrukerproblematikk og databaseadministrasjon, og kan gjøre rede for disse- forstår hvordan innebygd funksjonalitet i relasjonsdatabasesystem kan utnyttes i en klient/tjener-arkitektur- vet hvordan ulike typer data kan lagres og representeres i et databasesystem; tekst, XML og temporale data.- kan gjøre rede for hvordan NoSQL-løsninger er et alternativ til relasjonsdatabaser i Web-løsninger FERDIGHETERKandidaten:- kan administrere en flerbrukerdatabase med SQL-kommandoer i et valgt databaseverktøy- lager sin egen (mest mulig normaliserte) relasjonsdatabase med nøkler og referanseintegritet som ikke bare lagrer strukturelle data, men også tekst og semi-strukturelle data (XML)- kan utnytte databaseverktøyet funksjonalitet til utvidet bruk av SQL i en klient/tjener-sammenheng for å støtte opp rundt applikasjoner mot databasen- kan utnytte databaseverktøyet til å lagre temporale data- kan utføre SQL-spørringer mot ulike typer data i en database GENERELL KOMPETANSEKandidaten:- viser en bevisst holdning til lagring og representasjon av ulike typer data i et informasjonssystem- viser en bevisst holdning til databasedesign for å unngå unødvendig dobbeltlagring av data i en database Innhold:Installering og bruk av valgt databaseverktøy (MySQL). Flerbrukerproblematikk og databaseadministrasjon (DBA) i SQL. Bruk av SQL og innebygd funksjonalitet i databaseverktøyet (bruk av funksjoner/prosedyrer og triggere). Utnytte databaseverktøyet i en klient/tjener -arkitektur. Se på forholdet database - applikasjon. Lagring av ulike typer data; tekst, XML (semi-strukturelle data), dato/tid (temporale data). Enkel bruk av NoSQL-løsning. MySQL blir brukt i eksempler, men noen utfyllende eksempler i Oracle kan forekomme i lærestoffet.Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Databaser 2 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

COURSE OVERVIEW Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. TARGET AUDIENCE The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure. COURSE OBJECTIVES   Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics COURSE CONTENT Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Introduction to Azure Synapse Analytics Describe Azure Databricks Introduction to Azure Data Lake storage Describe Delta Lake architecture Work with data streams by using Azure Stream Analytics Lab 1: Explore compute and storage options for data engineering workloads Combine streaming and batch processing with a single pipeline Organize the data lake into levels of file transformation Index data lake storage for query and workload acceleration After completing module 1, students will be able to: Describe Azure Synapse Analytics Describe Azure Databricks Describe Azure Data Lake storage Describe Delta Lake architecture Describe Azure Stream Analytics Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Design a multidimensional schema to optimize analytical workloads Code-free transformation at scale with Azure Data Factory Populate slowly changing dimensions in Azure Synapse Analytics pipelines Lab 2: Designing and Implementing the Serving Layer Design a star schema for analytical workloads Populate slowly changing dimensions with Azure Data Factory and mapping data flows After completing module 2, students will be able to: Design a star schema for analytical workloads Populate a slowly changing dimensions with Azure Data Factory and mapping data flows Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Lab 3: Data engineering considerations Managing files in an Azure data lake Securing files stored in an Azure data lake After completing module 3, students will be able to: Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Explore Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Lab 4: Run interactive queries using serverless SQL pools Query Parquet data with serverless SQL pools Create external tables for Parquet and CSV files Create views with serverless SQL pools Secure access to data in a data lake when using serverless SQL pools Configure data lake security using Role-Based Access Control (RBAC) and Access Control List After completing module 4, students will be able to: Understand Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Understand big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Lab 5: Explore, transform, and load data into the Data Warehouse using Apache Spark Perform Data Exploration in Synapse Studio Ingest data with Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Spark pools in Azure Synapse Analytics Integrate SQL and Spark pools in Azure Synapse Analytics After completing module 5, students will be able to: Describe big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Lab 6: Data Exploration and Transformation in Azure Databricks Use DataFrames in Azure Databricks to explore and filter data Cache a DataFrame for faster subsequent queries Remove duplicate data Manipulate date/time values Remove and rename DataFrame columns Aggregate data stored in a DataFrame After completing module 6, students will be able to: Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Lab 7: Ingest and load Data into the Data Warehouse Perform petabyte-scale ingestion with Azure Synapse Pipelines Import data with PolyBase and COPY using T-SQL Use data loading best practices in Azure Synapse Analytics After completing module 7, students will be able to: Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Data integration with Azure Data Factory or Azure Synapse Pipelines Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines Lab 8: Transform Data with Azure Data Factory or Azure Synapse Pipelines Execute code-free transformations at scale with Azure Synapse Pipelines Create data pipeline to import poorly formatted CSV files Create Mapping Data Flows After completing module 8, students will be able to: Perform data integration with Azure Data Factory Perform code-free transformation at scale with Azure Data Factory Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Orchestrate data movement and transformation in Azure Data Factory Lab 9: Orchestrate data movement and transformation in Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines After completing module 9, students will be able to: Orchestrate data movement and transformation in Azure Synapse Pipelines Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Lab 10: Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Understand developer features of Azure Synapse Analytics Optimize data warehouse query performance in Azure Synapse Analytics Improve query performance After completing module 10, students will be able to: Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Analyze and optimize data warehouse storage in Azure Synapse Analytics Lab 11: Analyze and Optimize Data Warehouse Storage Check for skewed data and space usage Understand column store storage details Study the impact of materialized views Explore rules for minimally logged operations After completing module 11, students will be able to: Analyze and optimize data warehouse storage in Azure Synapse Analytics Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark pools Query Azure Cosmos DB with serverless SQL pools Lab 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Synapse Analytics Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics After completing module 12, students will be able to: Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Lab 13: End-to-end security with Azure Synapse Analytics Secure Azure Synapse Analytics supporting infrastructure Secure the Azure Synapse Analytics workspace and managed services Secure Azure Synapse Analytics workspace data After completing module 13, students will be able to: Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Lab 14: Real-time Stream Processing with Stream Analytics Use Stream Analytics to process real-time data from Event Hubs Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics Scale the Azure Stream Analytics job to increase throughput through partitioning Repartition the stream input to optimize parallelization After completing module 14, students will be able to: Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Process streaming data with Azure Databricks structured streaming Lab 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks Explore key features and uses of Structured Streaming Stream data from a file and write it out to a distributed file system Use sliding windows to aggregate over chunks of data rather than all data Apply watermarking to remove stale data Connect to Event Hubs read and write streams After completing module 15, students will be able to: Process streaming data with Azure Databricks structured streaming Module 16: Build reports using Power BI integration with Azure Synpase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Create reports with Power BI using its integration with Azure Synapse Analytics Lab 16: Build reports using Power BI integration with Azure Synpase Analytics Integrate an Azure Synapse workspace and Power BI Optimize integration with Power BI Improve query performance with materialized views and result-set caching Visualize data with SQL serverless and create a Power BI report After completing module 16, students will be able to: Create reports with Power BI using its integration with Azure Synapse Analytics Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. Use the integrated machine learning process in Azure Synapse Analytics Lab 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics Create an Azure Machine Learning linked service Trigger an Auto ML experiment using data from a Spark table Enrich data using trained models Serve prediction results using Power BI After completing module 17, students will be able to: Use the integrated machine learning process in Azure Synapse Analytics     [-]

. Students will also learn how to design and architect solutions using zero trust principles and specify security requirements for cloud infrastructure in different service models (SaaS, PaaS, IaaS). TARGET AUDIENCE IT professionals with advanced experience and knowledge in a wide range of security engineering areas, including identity and access, platform protection, security operations, securing data, and securing applications. They should also have experience with hybrid and cloud implementations. COURSE OBJECTIVES Design a Zero Trust strategy and architecture Evaluate Governance Risk Compliance (GRC) technical strategies and security operations strategies Design security for infrastructure Design a strategy for data and applications COURSE CONTENT Module 1: Build an overall security strategy and architecture Learn how to build an overall security strategy and architecture. Lessons M1 Introduction Zero Trust overview Develop Integration points in an architecture Develop security requirements based on business goals Translate security requirements into technical capabilities Design security for a resiliency strategy Design a security strategy for hybrid and multi-tenant environments Design technical and governance strategies for traffic filtering and segmentation Understand security for protocols Exercise: Build an overall security strategy and architecture Knowledge check Summary After completing module 1, students will be able to: Develop Integration points in an architecture Develop security requirements based on business goals Translate security requirements into technical capabilities Design security for a resiliency strategy Design security strategy for hybrid and multi-tenant environments Design technical and governance strategies for traffic filtering and segmentation Module 2: Design a security operations strategy Learn how to design a security operations strategy. Lessons M2 Introduction Understand security operations frameworks, processes, and procedures Design a logging and auditing security strategy Develop security operations for hybrid and multi-cloud environments Design a strategy for Security Information and Event Management (SIEM) and Security Orchestration, Evaluate security workflows Review security strategies for incident management Evaluate security operations strategy for sharing technical threat intelligence Monitor sources for insights on threats and mitigations After completing module 2, students will be able to: Design a logging and auditing security strategy Develop security operations for hybrid and multi-cloud environments. Design a strategy for Security Information and Event Management (SIEM) and Security Orchestration, A Evaluate security workflows. Review security strategies for incident management. Evaluate security operations for technical threat intelligence. Monitor sources for insights on threats and mitigations. Module 3: Design an identity security strategy Learn how to design an identity security strategy. Lessons M3 Introduction Secure access to cloud resources Recommend an identity store for security Recommend secure authentication and security authorization strategies Secure conditional access Design a strategy for role assignment and delegation Define Identity governance for access reviews and entitlement management Design a security strategy for privileged role access to infrastructure Design a security strategy for privileged activities Understand security for protocols After completing module 3, students will be able to: Recommend an identity store for security. Recommend secure authentication and security authorization strategies. Secure conditional access. Design a strategy for role assignment and delegation. Define Identity governance for access reviews and entitlement management. Design a security strategy for privileged role access to infrastructure. Design a security strategy for privileged access. Module 4: Evaluate a regulatory compliance strategy Learn how to evaluate a regulatory compliance strategy. Lessons M4 Introduction Interpret compliance requirements and their technical capabilities Evaluate infrastructure compliance by using Microsoft Defender for Cloud Interpret compliance scores and recommend actions to resolve issues or improve security Design and validate implementation of Azure Policy Design for data residency Requirements Translate privacy requirements into requirements for security solutions After completing module 4, students will be able to: Interpret compliance requirements and their technical capabilities Evaluate infrastructure compliance by using Microsoft Defender for Cloud Interpret compliance scores and recommend actions to resolve issues or improve security Design and validate implementation of Azure Policy Design for data residency requirements Translate privacy requirements into requirements for security solutions Module 5: Evaluate security posture and recommend technical strategies to manage risk Learn how to evaluate security posture and recommend technical strategies to manage risk. Lessons M5 Introduction Evaluate security postures by using benchmarks Evaluate security postures by using Microsoft Defender for Cloud Evaluate security postures by using Secure Scores Evaluate security hygiene of Cloud Workloads Design security for an Azure Landing Zone Interpret technical threat intelligence and recommend risk mitigations Recommend security capabilities or controls to mitigate identified risks After completing module 5, students will be able to: Evaluate security postures by using benchmarks Evaluate security postures by using Microsoft Defender for Cloud Evaluate security postures by using Secure Scores Evaluate security hygiene of Cloud Workloads Design security for an Azure Landing Zone Interpret technical threat intelligence and recommend risk mitigations Recommend security capabilities or controls to mitigate identified risks Module 6: Understand architecture best practices and how they are changing with the Cloud Learn about architecture best practices and how they are changing with the Cloud. Lessons M6 Introduction Plan and implement a security strategy across teams Establish a strategy and process for proactive and continuous evolution of a security strategy Understand network protocols and best practices for network segmentation and traffic filtering After completing module 6, students will be able to: Describe best practices for network segmentation and traffic filtering. Plan and implement a security strategy across teams. Establish a strategy and process for proactive and continuous evaluation of security strategy. Module 7: Design a strategy for securing server and client endpoints Learn how to design a strategy for securing server and client endpoints. Lessons M7 Introduction Specify security baselines for server and client endpoints Specify security requirements for servers Specify security requirements for mobile devices and clients Specify requirements for securing Active Directory Domain Services Design a strategy to manage secrets, keys, and certificates Design a strategy for secure remote access Understand security operations frameworks, processes, and procedures Understand deep forensics procedures by resource type After completing module 7, students will be able to: Specify security baselines for server and client endpoints Specify security requirements for servers Specify security requirements for mobile devices and clients Specify requirements for securing Active Directory Domain Services Design a strategy to manage secrets, keys, and certificates Design a strategy for secure remote access Understand security operations frameworks, processes, and procedures Understand deep forensics procedures by resource type Module 8: Design a strategy for securing PaaS, IaaS, and SaaS services Learn how to design a strategy for securing PaaS, IaaS, and SaaS services. Lessons M8 Introduction Specify security baselines for PaaS services Specify security baselines for IaaS services Specify security baselines for SaaS services Specify security requirements for IoT workloads Specify security requirements for data workloads Specify security requirements for web workloads Specify security requirements for storage workloads Specify security requirements for containers Specify security requirements for container orchestration After completing module 8, students will be able to: Specify security baselines for PaaS, SaaS and IaaS services Specify security requirements for IoT, data, storage, and web workloads Specify security requirements for containers and container orchestration Module 9: Specify security requirements for applications Learn how to specify security requirements for applications. Lessons M9 Introduction Understand application threat modeling Specify priorities for mitigating threats to applications Specify a security standard for onboarding a new application Specify a security strategy for applications and APIs After completing module 9, students will be able to: Specify priorities for mitigating threats to applications Specify a security standard for onboarding a new application Specify a security strategy for applications and APIs Module 10: Design a strategy for securing data Learn how to design a strategy for securing data. Lessons M10 Introduction Prioritize mitigating threats to data Design a strategy to identify and protect sensitive data Specify an encryption standard for data at rest and in motion After completing module 10, students will be able to: Prioritize mitigating threats to data Design a strategy to identify and protect sensitive data Specify an encryption standard for data at rest and in motion [-]

Målsetting Hensikten med opplæringen er å gi traverskranførere en god teoretisk grunnopplæring i sikker bruk av traverskraner, slik at uhell og ulykker i forbindelse med løfteoperasjoner unngåsOpplæringen skal gi kandidatene god innsikt i prinsippene for traverskranens konstruksjon, virkemåte, vedlikehold og bruk. Praktisk forståelse for prinsippene for kranens konstruksjon, virkemåte, montering, kjøremåte, løftekapasitet og sikkerhetsutstyr mot overlastArbeidsoppgaver vil kunne kompensere for noen timer. Emneliste Innledning Modul 2.3 Løfteredskap (O-1.1) Krav til kranfører Bruksområder for traverskraner Ulykker med bro- og traverskraner Oppbygging av forskjellige typer bro- og traverskraner Hovedkomponenter på bro- og traverskraner Elektrisk og hydraulisk anlegg Sikkerhetsbrytere (Overlastbryter) Ståltau/blokk Sertifisering/dokumentasjon Kontroll og vedlikehold Arbeidsoppgaver Praktisk bruk av løfteredskap Øvingsoppgaver Kjøreteknikk Eksamen Avslutningsprøve Teori min. 30 spørsmålPraktisk prøve gjennomføres etter at kandidaten har i tråd med fadderavtale dokumentert min. 40 timer praksis Kompetansebevis / sertifikat Et kursbevis vil bli utstedt til hver kandidat som har gjennomført og bestått opplæringen.Kursbeviset vil inneholde informasjon om opplæringssted, kursinnhold, dato for gjennomføring, kandidatens navn og fødselsdato og være signert av daglig leder/kurs koordinator Pris er per deltaker og inkluderer alle kursdager, eksamen samt lunsj i vår kantine. [-]

https://www.glasspaper.no/kurs/kepnertregoe/ [-]

Byggdrifterfaget er et studium på yrkesfaglig studieretning ved NooA videregående skole   En byggdrifter, også kalt vaktmester eller driftsoperatør, drifter og vedlikeholder lokaler, inventar og utstyr i et bygg. Byggdrifteren tar seg av vedlikehold og mindre reparasjoner, mens andre fagfolk tar seg av større problemer ved bygg og anlegg.     [-]

OversiktEngelsk er et nøkkelspråk for internasjonal forretning, samarbeid og kommunikasjon. Ved NLS Norwegian Language School tilbyr vi skreddersydde engelskkurs for bedrifter som ønsker å gi sine ansatte økt selvtillit i både muntlig og skriftlig engelsk – fra daglig kontorkommunikasjon til formelle presentasjoner og forhandlinger. Hvorfor er engelsk viktig for bedriften din? Global rekkevidde: Engelsk er verdens mest brukte forretningsspråk og gir tilgang til nye markeder og partnere. Styrket omdømme: Dyktige engelskspråklige ansatte gir et profesjonelt inntrykk utad. Effektiv internkommunikasjon: Lettere samhandling med internasjonale kolleger og avdelinger. Kursopplegg Innledende behovskartlegging: Vi undersøker språknivå og mål – for eksempel skriftlig forretningskorrespondanse, møter eller salgsaktiviteter. Tilpasset innhold: Bransjerelevante case-studier og rollespill som sikrer praktisk læring. Løpende vurdering: Jevnlig feedback og tester sikrer at deltakerne utvikler seg i ønsket tempo. Fleksible løsninger: Vi tilbyr både intensive kurs og semesterbaserte opplegg over lengre tid. Undervisningsalternativer På arbeidsplassen: Vår instruktør kommer til dere, noe som gir enkel koordinering. Hos NLS Norwegian Language School: Et strukturert læringsmiljø midt i Oslo. På nett: Virtuelle klasser som passer for spredte eller reiseglade team. Kontakt ossKlar for å løfte bedriftens engelskspråklige ferdigheter? Kontakt oss for mer informasjon og et skreddersydd kursopplegg. E-post: info@nlsnorwegian.no TelefonMer informasjon: +47 90814756 Mer informasjon:  https://nlsnorwegian.no/no/engelskkurs-for-bedrifter/ [-]

ITIL® Strategist - Direct, Plan and Improve [-]

COURSE OVERVIEW The Certified Information Systems Security Professional (CISSP) is the most globally recognized certification in the cybersecurity market. CISSP validates a cybersecurity professional’s deep technical and managerial knowledge and experience to effectively design, engineer and manage an organization’s overall security posture. Please note an exam voucher is included as part of this course TARGET AUDIENCE Cybersecurity professionals with at least 5 years in the information security field. Member data has shown that amajority of CISSP holders are in middle management and a much smaller proportion are in senior or junior/entry-level positions. Roles include:• Chief Information Officer• Chief Information Security Officer• Chief Technology Officer• Compliance Manager / Officer• Director of Security• Information Architect• Information Manager / Information RiskManager or Consultant• IT Specialist / Director / Manager• Network / System Administrator• Security Administrator• Security Architect / Security Analyst• Security Consultant• Security Manager• Security Systems Engineer / Security EngineerSectorsCISSP is relevant across all sectors and industries, including:• Aerospace• Automotive• Banking, financial services, insurance (BFSI)• Construction• Cybersecurity• Energy• Engineering• Government• Healthcare, IT products, services, consulting• Manufacturing• Pharma• Retail• Telecom COURSE OBJECTIVESAfter completing this course you should be able to: Understand and apply fundamental concepts and methods related to the fields of information technology and security Align overall organizational operational goals with security functions and implementations. Understand how to protect assets of the organization as they go through their lifecycle. Understand the concepts, principles, structures and standards used to design, implement, monitor and secure operating systems, equipment, networks, applications and those controls used to enforce various levels of confidentiality, integrity and availability. Implement system security through the application of security design principles and application of appropriate security control mitigations for vulnerabilities present in common information system types and architectures. Understand the importance of cryptography and the security services it can provide in today’s digital and information age. Understand the impact of physical security elements on information system security and apply secure design principles to evaluate or recommend appropriate physical security protections. Understand the elements that comprise communication and network security coupled with a thorough description of how the communication and network systems function. List the concepts and architecture that define the associated technology and implementation systems and protocols at Open Systems Interconnection (OSI) model layers 1-7. Identify standard terms for applying physical and logical access controls to environments related to their security practice. Appraise various access control models to meet business security requirements. Name primary methods for designing and validating test and audit strategies that support business requirements. Enhance and optimize an organization’s operational function and capacity by applying and utilizing appropriate security controls and countermeasures. Recognize risks to an organization’s operational endeavours and assess specific threats, vulnerabilities and controls. Understand the System Lifecycle (SLC) and the Software Development Lifecycle (SDLC) and how to apply security to it; identify which security control(s) are appropriate for the development environment; and assess the effectiveness of software security. COURSE CONTENT Domain 1: Security and Risk Management Domain 2: Asset Security Domain 3: Security Architecture and Engineering Domain 4: Communication and Network Security Domain 5: Identity and Access Management (IAM) Domain 6: Security Assessment and Testing Domain 7: Security Operations Domain 8: Software Development Security TEST CERTIFICATION Recommended as preparation for the following exam: (ISC)2 Certified Information Systems Security Professional Gaining this accreditation is not just about passing the exam, there are a number of other criteria that need to be met including 5 years of cumulative, paid work experience in two or more of the eight domains of the (ISC)²® CISSP CBK . Full details can be found at https://www.isc2.org/cissp/default.aspx Those without the required experience can take the exam to become an Associate of (ISC)²  while working towards the experience needed for full certification Please note an exam voucher is included as part of this course   [-]