Oversikt over relevante kurs innen IT-kurs i Ängaryd

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 [-]

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     [-]

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 [-]

AutoCAD 3D introduksjonskurs: Deltagerne skal kunne skille mellom ulike modelltyper, og kjenne til grunnprinsipper for 3D-modellering og bruk av koordinatsystem, samt beherske bruk av betraktningsvinkler og skjermnavigering. Koordinatsystemer Angivelse av punkter i rommet Solid modellering Surface modellering Mesh modellering Sette opp Layout i paperspace, projeksjoner og snitt Lagstruktur og lagdefinisjon, farger, linjetyper, målsetting Lyssetting, naturlig sollys og lokale lyskilder Knytte materialer til objekt eller til lag Renderfunksjoner Animasjon og video [-]

Fleksible kurs for fremtidenNy kunnskap skal gi umiddelbar effekt, og samtidig være holdbar og bærekraftig på lang sikt. NTI AS har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon.   AutoCAD plant 3D grunnkurs  Her er et utvalg av temaene du vil lære på kurset: Prosjektoppsetning og Modullinjer/net Design av stålkonstruksjoner Utstyr (opprettelse av utstyr og import av utstyr bl.a. fra Inventor) Rørdesign i 3D-modellen Redigering av stål, utstyr og rørtrekk Opprettelse av arrangementstegninger og rørisometritegninger  Uttrekk av mengdedata i listeform Kurset  gir  en innføring i systemets oppbygging med rørdesign i sentrum. Videre gjennomgås de enkelte modulene i henhold til følgende arbeidsflyt: P&ID. Integrert i løsningen er velkjente AutoCAD P&ID og vi tar utgangspunkt i et enkelt flytdiagram som representerer det skjematiske designet for minifabrikken vi skal modellere Stål/Struktur. Tilpassete kurs for bedrifterVi vil at kundene våre skal være best på det de gjør - hele tiden.  Derfor tenker vi langsiktig om kompetanseutvikling og ser regelmessig kunnskapsløft som en naturlig del av en virksomhet. Vårt kurskonsept bygger på et moderne sett av ulike læringsmiljøer, som gjør det enkelt å finne riktig løsning uansett behov. Ta kontakt med oss på telefon 483 12 300, epost: salg@nticad.no eller les mer på www.nticad.no   [-]

GeT Everything NTI tilbyr eLæringkurs av høyeste kvalitet. Uansett hvilket kurs du velger har du tilgang til dem 24/7 i 1 år (365 dager). Med elæringskurs velger du selv ditt tempo i læringen, og om du vil lære gjennom kombinasjon av å se, lese, lytte og teste selv – eller hvorfor ikke en kombinasjon av flere? Det du trenger er en PC, smarttelefon eller nettbrett som har internettilgang   Her er et utvalg av kursene du får tilgang på: Autodesk Adobe Primavera Bluebeam Bentlye Microsof Trimble McNeel NTI  leverer opplæring for å forenkle og effektivisere din arbeidshverdag Vi har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon. Global eTraining har over 25 års erfaring med opplæring, og har solgt millioner av elæringskurs i over 150 land.  PC, smarttelefon eller nettbrett som har internettilgang Pål har gjennomført e-læringskurs Pål hadde ikke anledning til å reise bort en uke for å delta på kurs, da var det forlokkende å gjennomføre kurset som e-læringskurs. Kurset var absolutt verdt pengene. Det var en viktig bekreftelse på at jeg har basiskunnskapene. Jeg lærte mange nye viktige kommandoer for å gjøre operasjoner mer effektivt, fikk også en pekepinn på hvor jeg kan bygge på med kunnskap.Les mer her [-]

. 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 [-]

Kursinnhold Gjennomgang av Excel vinduet Enkle formler Enkel formatering Klipp og lim Kopiering av formler Merking Slette data Fjerne og legge til celler, rader og kolonner Angre Flytting og kopiering Søk og erstatt Autofyll Cellereferanser Låse og gi navn til celler Hva er en funksjon? Funksjonsveiviseren Gjennomgang av de mest brukte funksjonene: Summer, antall, størst, min og gjennomsnitt. Målgruppe Deg som Har begynt i en stilling hvor en er forventet å kunne Excel Er nysgjerrig på hva Excel kan gjøre for deg i din jobb Er nybegynner eller litt øvet Sliter med å skjønne hvordan du kan jobbe mest effektivt i Excel Forkunnskaper Excel: Ingen Øvrig: Er kjent med bruk av PC Det er fordelaktig å ha to skjermer - en til å følge kurset og en til å gjøre det kursholder demonstrerer. Kurset gjennomføres i sanntid med nettundervisning via Teams. Det blir mulighet for å stille spørsmål, ha diskusjoner, demonstrasjoner og øvelser. Du vil motta en invitasjon til Teams fra kursholder. [-]

COURSE OVERVIEW . With extensive hands-on-labs, the class enables administrators and engineers to effectively manage data in an ever-changing technical and business environment, bringing tangible benefit to businesses in the digital world. This course is based on Veeam Availability Suite v11. TARGET AUDIENCE This course is suitable for anyone responsible for configuring, managing or supporting a Veeam Availability Suite v11 environment. COURSE OBJECTIVES After completing this course, attendees should be able to: Describe Veeam Availability Suite components usage scenarios and relevance to your environment. Effectively manage data availability in on-site, off-site, cloud and hybrid environments. Ensure both Recovery Time Objectives (RTOs) and Recovery Point Objectives (RPOs) are met. Configure Veeam Availability Suite to ensure data is protected effectively. Adapt with an organization’s evolving technical and business data protection needs. Ensure recovery is possible, effective, efficient, secure and compliant with business requirements. Provide visibility of the business data assets, reports and dashboards to monitor performance and risks. COURSE CONTENT Introduction Describe RTOs and RPOs, what they mean for your business, how to manage and monitor performance against them The 3-2-1 Rule and its importance in formulating a successful backup strategy Identify key Veeam Availability Suite components and describe their usage scenarios and deployment types Building Backup Capabilities Backup methods, the appropriate use cases and impact on underlying file systems Create, modify, optimize and delete backup jobs, including Agents and NAS Backup jobs. Explore different tools and methods to maximize environment performance Ensure efficiency by being able to select appropriate transport modes while being aware of the impact of various backup functions on the infrastructure Building Replication Capabilities Identify and describe the options available for replication and impacts of using them Create and modify replication jobs, outline considerations to ensure success Introduce the new Continuous Data Protection (CDP) policy Secondary Backups Simple vs. advanced backup copy jobs, how to create and modify them using best practices to ensure efficient recovery Discuss using tapes for backups Advanced Repository Capabilities Ensure repository scalability using a capability such as SOBR on-premises and off-site including integration with cloud storage Ensure compatibility with existing deduplication appliances Introduce the new hardened repository Protecting Data in the Cloud Review how Veeam can protect the data of a cloud native application Review how Veeam Cloud Connect enables you to take advantage of cloud services built on Veeam Review how Veeam can be used to protect your Office 365 data Restoring from Backup Ensure you have the confidence to use the correct restore tool at the right time for restoring VMs, bare metal and individual content such as files and folders Utilize Secure Restore to prevent the restoration of malware Describe how to use Staged Restore to comply with things like General Data Protection Regulation (GDPR) before releasing restores to production Identify, describe and utilize the different explores and instant recovery tools and features Recovery from Replica Identify and describe in detail, failover features and the appropriate usage Develop, prepare and test failover plans to ensure recovery Disaster recovery from replica to meet a variety of real-world recovery needs Testing Backup and Replication Testing backups and replicas to ensure you can recover, what you need, when you need to Configure and setup virtual sandbox environments based on backup, replicas and storage snapshots Veeam Backup Enterprise Manager and Veeam ONE Introduce the concept of monitoring your virtual, physical and cloud environments with Veeam Backup Enterprise Manager and Veeam ONE™ Configuration Backup Locate, migrate or restore backup configuration   TEST CERTIFICATION Completion of this course satisfies the prerequisite for taking the Veeam Certified Engineer (VMCE) 2021 exam. [-]

ISO/IEC 27701 Foundation [-]

Spring Boot Development [-]

Bruker du mye tid i Excel på å få gjort enkle arbeidsoppgaver? Kommer det til stadighet prosent og dato i celler hvor du vil ha vanlige tall? Blir en formel ødelagt når du flytter den? Er det vanskelig å lage det diagrammet du ønsker? Blir ikke utskriftene dine slik du ønsker? Dette er vanlige problemstillinger mange sliter med og som blir borte etter endt kurs! På kun 2 dager vil du mestre de vanligste formler og funksjoner du trenger i din arbeidsdag. Du lærer gode rutiner og hurtigtastene du trenger for å kunne arbeide raskt og effektivt. Du vil kunne bygge alt fra enkle til mer avanserte modeller og vil føle deg trygg på at modellen din virker og gir rett resultat. Du vil også få en rekke tips og triks du kan bruke i din arbeidsdag.  Alt du lærer får du repetert gjennom aktiv oppgaveløsning slik at du husker det du har lært når du kommer tilbake på jobb. Kursdokumentasjon, lunsj og pausemat er selvsagt inkludert!   Kursholderne har mer enn 20 års Excel erfaring som de gjerne deler med deg!   Kurset passer for deg med liten erfaring og som ønsker å lære Excel fra grunnen av. Kurset passer også for deg som er selvlært og som ønsker å jobbe mer effektivt. Meld deg på Excel-kurs allerede i dag og sikre deg plass!   Krav til forkunnskaper Grunnleggende kunnskaper i Windows.   Kursinnhold Redigering Merking Sletting Angre muligheter Flytting og kopiering Innsetting og sletting Formler Bruk av formler Autofyll Cellereferanser Formatering Hva er formatering? Kolonnebredde og radhøyde Tallformatering Skriftformatering Justering av celleinnhold Kantlinjer og fyllfarger Betinget formatering Funksjoner Bruk av funksjoner Summering Minst, størst, antall og gjennomsnitt Hvis-funksjonen Betinget summering Diagram Utforming av diagram Diagramtyper Flere regneark Arbeid med regneark Innsetting og sletting av regneark Flytting og kopiering av regneark Referering til andre regneark Enkle formler på tvers av ark Vindus håndtering Lister og tabeller Sortering Tabeller Filtrering Deling og frysing av vindu   [-]

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

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Erfaring med programmering i et objektorientert språk. Innleveringer: Det blir gitt 10 øvinger. 8 må være godkjente for å gå opp til eksamen. Personlig veileder: ja Vurderingsform: individuell skriftlig eksamen, 3 timer. Ansvarlig: Tore Berg Hansen Eksamensdato: 17.12.13 / 20.05.14         Læremål: Etter å ha gjennomført emnet skal kandidaten ha følgende samlete læringsutbytte: KUNNSKAPER:Kandidaten kan forklare:- hva .NET-rammeverket er, dets hensikt og hva det inneholder- begrepene Common Language Runtime, Common Type System og managed code- begrepene Solution, Project og Assembly- hva en webtjeneste er- hvordan datakilder kan aksesseres ved hjelp av ADO.NET- hvordan webapplikasjoner kan lages ved hjelp av ASP.NET FERDIGHETER:Kandidaten:- kan skrive korte programmer i C#, Visual Basic .NET og C++/managed C++ som viser bruk av de sentrale konsepter som klassebiblioteket, ADO.NET og ASP.NET GENERELL KOMPETANSE:Kandidaten:- er klar over at .NET rammeverket har styrker og svakheter og at det finnes alternative teknologier Innhold:.NET-rammeverket og arkitekturen. Common Language Runtime (CLR). Common Type System (CTS). Klassebiblioteket. Common Language Specification (CLS). Assemblies. Programmeringsspråkene C#, C++, Visual Basic.NET. Managed code. Web services. ADO.NET. ASP.NET.Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Applikasjonsutvikling på .NET-plattformen 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]