Oversikt over relevante kurs innen IT-kurs i Svelvik

Understand the purpose and key concepts of Information Security Management, elucidating its significance in safeguarding the confidentiality, integrity, and availability of organisational information assets. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. After completing this course, students will be able to: Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics Course prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.Recommended prerequisites:M-DP900 - Microsoft Azure Data FundamentalsM-AZ900 - Microsoft Azure Fundamentals Agenda Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Module 16: Build reports using Power BI integration with Azure Synapase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. [-]

Kursinnhold Enkle formler Cellereferanser Gi navn til celler og områder Feilkontroll og formelrevisjon Hente data fra andre ark og arbeidsbøker Egendefinerte tallformater Betinget formatering Utklippstavle og avansert innliming   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. [-]

Er du på jakt etter mer avansert funksjonalitet på forsidene dine? På dette webinaret lærer du mer om å sette inn innhold fra andre kilder og å sy sammen komponentene på siden. Webinaret varer i 2 timer og består av to økter à 45 min. Etter hver økt er det 10 min spørsmålsrunde. Mellom øktene er det 10 min pause. Webinaret kan også spesialtilpasses og holdes bedriftsinternt kun for din bedrift.   Kursinnhold:   Sider og sideoppsett Bli kjent med Webdel-sider og oppsett Hvordan legge til skriptsnutter og elementer fra andre nettsider   Bygg inn innhold Legg inn embed-kode Forberede og presentere en PowerPoint-presentasjon på forsiden ved hjelp av Office Web Apps/Office Online   Forsider og dashboards Forberede og presentere en Excel-bok på forsiden med Excel Services Forberede og presentere en Visio-tegning som forsidemeny med Visio Services   Dynamiske sider Målgrupper Koble sammen webdeler og la innhold i en webdel påvirke innholdet i en annen   3 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Gratis support [-]

Ønsker du å jobbe med ulike tegninger i Visio, men føler du ikke mestrer programmet? Vil du i tillegg kunne lage egne maler for å jobbe mer effektivt? Da er ”Visio Grunnleggende” kurset for deg! Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1    Hva er Visio? Få oversikt. Bli kjent med programvinduet og hvordan du kan tilpasse det etter dine behov. Mal. Hvordan er en mal bygd opp og hvordan jobbe med en tegning? Formatering. Lær å formatere og hva formateringsbegrepet betyr. Sjablonger og figurer. Hva er sjablonger og figurer?   Å jobbe effektivt med Visio Bygge opp en tegning. Lær å bygge opp en tegning fra bunnen av. Hurtigtaster. Effektiv bruk av tastatur og mus. Formatering. Bruk formatering for å gjøre tegningene oversiktlige og informasjonen mest mulig tilgjengelig. Ark. Lær å jobbe med flere ark, navngi dem, slette dem, bruke bakgrunner etc. Praktisk oppgaveløsing. Jobb med skreddersydde oppgaver innenfor dagens temaer. Andre Office-programmer. Lær å bruke Visio-tegninger i andre Office-programmer.   Flytskjema og organisasjonskart Koblinger. Lær å koble figurer på en effektiv måte. Oppsett. Hvordan sørge for at figurene står plassert på en nøyaktig og oversiktlig måte? Navigasjon. Bygge opp praktisk navigasjon mellom sidene i en større tegning.   Dag 2    Nettverksdiagram Figurdata. Knytt praktisk informasjon til figurene i tegningen. Rapporter. Hvordan hente ut rapporter fra en tegning?   Prosjektplaner Tidslinje. Illustrere faser i et prosjekt på en oversiktlig måte. Gantt-diagram. Vise prosjektinformasjon på en mer detaljert måte. Utskrift. Få oversikt over de vanligste problemstillingene ved utskrift.   Egne maler Maler. Hva er maler, deres styrke og hvordan kan jeg utnytte dem best mulig i mitt arbeid? Sjablonger. Bygge opp en egen samling med de figurene du skal bruke. Figurer. Lær å lage egne tilpassede figurer. Praktisk oppgaveløsing. Jobb med skreddersydde oppgaver innenfor dagens temaer.   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

ITIL® 4 Practitioner: Change Enablement [-]

OneNote er et program fra Microsoft som gir deg mulighet til å digitalisere dine notater. Programmet egner seg særlig for deg som har behov for å skrive møtenotater, foredragsnotater og arbeidsnotater. OneNote vil synkronisere dine notater på tvers av dine enheter, og kan benyttes på din PC, din smarttelefon eller nettbrett. Du kan bygge inn tekst og filer fra Outlook, Word, Excel og PowerPoint, samt film- og lydfiler. Har du oversikten over notater etter at møter er over? Føler du at de papirbaserte notatene over tid blir uoversiktlige og lite tilgjengelige. Du kan jobbe raskere, smartere og bedre ved å ta i bruk OneNote. I dine digitale notater i OneNote kan du inkludere tekst, bilder, lenker til filer og websider, lyd og film. Du kan ta notater fra din smarttelefon, ditt nettbrett eller din PC; alt etter hva du har tilgjengelig. Systemet vil synkronisere notatene på tvers av dine enheter. OneNote er en del av Microsoft Office og er tilgjengelig gratis for alle.  Kurset kan spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler. Deltakere må ha med egen datamaskin med relevant programvare. 6 gode grunner til å delta Du vil se hvor enkelt det er å ta raske notater Lær hvordan du finner igjen notater raskt og effektivt Du vil kunne koble notater til oppgaver i Outlook Lær å holde møtenotater koblet til avtaler og møter i Outlook Få en innføring i hvordan flere kan jobbe samtidig med notater Lær hvordan OneNote kobler lyd/videoopptak med notater Synkroniser dine notater mellom dine enheter (PC, mobil, nettbrett) Forkunnskap: Erfaring i bruk av Microsoft Office. Varighet:3 timer Pris:3200 kroner Ansatte ved UiS har egne betalingsbetingelser. [-]

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.   Revit Architecture Basis I Her er et utvalg av temaene du vil lære på kurset: Introduksjon til BIM Modellering av 3D-bygningsmodell i flere detaljeringsgrader (informasjonsnivåer) Samarbeid med andre fagmodeller Generering av planer, snitt, fasader, detaljer og perspektiver Skjemaer og mengdeuttrekk Oppsetning til print A Anvendelse av relevante NTItools Kurset gir deg innblikk i bruken av BIM-arbeidsmetoder med Revit som hovedverktøy. Det bygges opp en full, parametrisk 3D-modell, hvor de grunnleggende funksjonene i Revit benyttes. DU vil få en bred forståelse av både prinsipper og funksjoner i Revit og skal bli i stand til å øke detaljeringen av prosjektet ytterligere.   Dette er et populært kurs, meld deg på nå!   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 [-]

SDWFND: Cisco SD WAN Operation and Deployment [-]

Implementing REST Services using Web API [-]

COURSE OVERVIEW Learn how to investigate, respond to, and hunt for threats using Microsoft Azure Sentinel, Azure Defender, and Microsoft 365 Defender. In this course you will learn how to mitigate cyberthreats using these technologies. Specifically, you will configure and use Azure Sentinel as well as utilize Kusto Query Language (KQL) to perform detection, analysis, and reporting. The course was designed for people who work in a Security Operations job role and helps learners prepare for the exam SC-200: Microsoft Security Operations Analyst. TARGET AUDIENCE The Microsoft Security Operations Analyst collaborates with organizational stakeholders to secure information technology systems for the organization. Their goal is to reduce organizational risk by rapidly remediating active attacks in the environment, advising on improvements to threat protection practices, and referring violations of organizational policies to appropriate stakeholders. Responsibilities include threat management, monitoring, and response by using a variety of security solutions across their environment. The role primarily investigates, responds to, and hunts for threats using Microsoft Azure Sentinel, Azure Defender, Microsoft 365 Defender, and third-party security products. Since the Security Operations Analyst consumes the operational output of these tools, they are also a critical stakeholder in the configuration and deployment of these technologies. COURSE OBJECTIVES Explain how Microsoft Defender for Endpoint can remediate risks in your environment Create a Microsoft Defender for Endpoint environment Configure Attack Surface Reduction rules on Windows 10 devices Perform actions on a device using Microsoft Defender for Endpoint Investigate domains and IP addresses in Microsoft Defender for Endpoint Investigate user accounts in Microsoft Defender for Endpoint Configure alert settings in Microsoft Defender for Endpoint Explain how the threat landscape is evolving Conduct advanced hunting in Microsoft 365 Defender Manage incidents in Microsoft 365 Defender Explain how Microsoft Defender for Identity can remediate risks in your environment. Investigate DLP alerts in Microsoft Cloud App Security Explain the types of actions you can take on an insider risk management case. Configure auto-provisioning in Azure Defender Remediate alerts in Azure Defender Construct KQL statements Filter searches based on event time, severity, domain, and other relevant data using KQL Extract data from unstructured string fields using KQL Manage an Azure Sentinel workspace Use KQL to access the watchlist in Azure Sentinel Manage threat indicators in Azure Sentinel Explain the Common Event Format and Syslog connector differences in Azure Sentinel Connect Azure Windows Virtual Machines to Azure Sentinel Configure Log Analytics agent to collect Sysmon events Create new analytics rules and queries using the analytics rule wizard Create a playbook to automate an incident response Use queries to hunt for threats Observe threats over time with livestream COURSE CONTENT Module 1: Mitigate threats using Microsoft Defender for Endpoint Implement the Microsoft Defender for Endpoint platform to detect, investigate, and respond to advanced threats. Learn how Microsoft Defender for Endpoint can help your organization stay secure. Learn how to deploy the Microsoft Defender for Endpoint environment, including onboarding devices and configuring security. Learn how to investigate incidents and alerts using Microsoft Defender for Endpoints. Perform advanced hunting and consult with threat experts. You will also learn how to configure automation in Microsoft Defender for Endpoint by managing environmental settings.. Lastly, you will learn about your environment's weaknesses by using Threat and Vulnerability Management in Microsoft Defender for Endpoint. Lessons M1 Protect against threats with Microsoft Defender for Endpoint Deploy the Microsoft Defender for Endpoint environment Implement Windows 10 security enhancements with Microsoft Defender for Endpoint Manage alerts and incidents in Microsoft Defender for Endpoint Perform device investigations in Microsoft Defender for Endpoint Perform actions on a device using Microsoft Defender for Endpoint Perform evidence and entities investigations using Microsoft Defender for Endpoint Configure and manage automation using Microsoft Defender for Endpoint Configure for alerts and detections in Microsoft Defender for Endpoint Utilize Threat and Vulnerability Management in Microsoft Defender for Endpoint Lab M1: Mitigate threats using Microsoft Defender for Endpoint Deploy Microsoft Defender for Endpoint Mitigate Attacks using Defender for Endpoint After completing module 1, students will be able to: Define the capabilities of Microsoft Defender for Endpoint Configure Microsoft Defender for Endpoint environment settings Configure Attack Surface Reduction rules on Windows 10 devices Investigate alerts in Microsoft Defender for Endpoint Describe device forensics information collected by Microsoft Defender for Endpoint Conduct forensics data collection using Microsoft Defender for Endpoint Investigate user accounts in Microsoft Defender for Endpoint Manage automation settings in Microsoft Defender for Endpoint Manage indicators in Microsoft Defender for Endpoint Describe Threat and Vulnerability Management in Microsoft Defender for Endpoint Module 2: Mitigate threats using Microsoft 365 Defender Analyze threat data across domains and rapidly remediate threats with built-in orchestration and automation in Microsoft 365 Defender. Learn about cybersecurity threats and how the new threat protection tools from Microsoft protect your organization’s users, devices, and data. Use the advanced detection and remediation of identity-based threats to protect your Azure Active Directory identities and applications from compromise. Lessons M2 Introduction to threat protection with Microsoft 365 Mitigate incidents using Microsoft 365 Defender Protect your identities with Azure AD Identity Protection Remediate risks with Microsoft Defender for Office 365 Safeguard your environment with Microsoft Defender for Identity Secure your cloud apps and services with Microsoft Cloud App Security Respond to data loss prevention alerts using Microsoft 365 Manage insider risk in Microsoft 365 Lab M2: Mitigate threats using Microsoft 365 Defender Mitigate Attacks with Microsoft 365 Defender After completing module 2, students will be able to: Explain how the threat landscape is evolving. Manage incidents in Microsoft 365 Defender Conduct advanced hunting in Microsoft 365 Defender Describe the investigation and remediation features of Azure Active Directory Identity Protection. Define the capabilities of Microsoft Defender for Endpoint. Explain how Microsoft Defender for Endpoint can remediate risks in your environment. Define the Cloud App Security framework Explain how Cloud Discovery helps you see what's going on in your organization Module 3: Mitigate threats using Azure Defender Use Azure Defender integrated with Azure Security Center, for Azure, hybrid cloud, and on-premises workload protection and security. Learn the purpose of Azure Defender, Azure Defender's relationship to Azure Security Center, and how to enable Azure Defender. You will also learn about the protections and detections provided by Azure Defender for each cloud workload. Learn how you can add Azure Defender capabilities to your hybrid environment. Lessons M3 Plan for cloud workload protections using Azure Defender Explain cloud workload protections in Azure Defender Connect Azure assets to Azure Defender Connect non-Azure resources to Azure Defender Remediate security alerts using Azure Defender Lab M3: Mitigate threats using Azure Defender Deploy Azure Defender Mitigate Attacks with Azure Defender After completing module 3, students will be able to: Describe Azure Defender features Explain Azure Security Center features Explain which workloads are protected by Azure Defender Explain how Azure Defender protections function Configure auto-provisioning in Azure Defender Describe manual provisioning in Azure Defender Connect non-Azure machines to Azure Defender Describe alerts in Azure Defender Remediate alerts in Azure Defender Automate responses in Azure Defender Module 4: Create queries for Azure Sentinel using Kusto Query Language (KQL) Write Kusto Query Language (KQL) statements to query log data to perform detections, analysis, and reporting in Azure Sentinel. This module will focus on the most used operators. The example KQL statements will showcase security related table queries. KQL is the query language used to perform analysis on data to create analytics, workbooks, and perform hunting in Azure Sentinel. Learn how basic KQL statement structure provides the foundation to build more complex statements. Learn how to summarize and visualize data with a KQL statement provides the foundation to build detections in Azure Sentinel. Learn how to use the Kusto Query Language (KQL) to manipulate string data ingested from log sources. Lessons M4 Construct KQL statements for Azure Sentinel Analyze query results using KQL Build multi-table statements using KQL Work with data in Azure Sentinel using Kusto Query Language Lab M4: Create queries for Azure Sentinel using Kusto Query Language (KQL) Construct Basic KQL Statements Analyze query results using KQL Build multi-table statements using KQL Work with string data using KQL statements After completing module 4, students will be able to: Construct KQL statements Search log files for security events using KQL Filter searches based on event time, severity, domain, and other relevant data using KQL Summarize data using KQL statements Render visualizations using KQL statements Extract data from unstructured string fields using KQL Extract data from structured string data using KQL Create Functions using KQL Module 5: Configure your Azure Sentinel environment Get started with Azure Sentinel by properly configuring the Azure Sentinel workspace. Traditional security information and event management (SIEM) systems typically take a long time to set up and configure. They're also not necessarily designed with cloud workloads in mind. Azure Sentinel enables you to start getting valuable security insights from your cloud and on-premises data quickly. This module helps you get started. Learn about the architecture of Azure Sentinel workspaces to ensure you configure your system to meet your organization's security operations requirements. As a Security Operations Analyst, you must understand the tables, fields, and data ingested in your workspace. Learn how to query the most used data tables in Azure Sentinel. Lessons M5 Introduction to Azure Sentinel Create and manage Azure Sentinel workspaces Query logs in Azure Sentinel Use watchlists in Azure Sentinel Utilize threat intelligence in Azure Sentinel Lab M5 : Configure your Azure Sentinel environment Create an Azure Sentinel Workspace Create a Watchlist Create a Threat Indicator After completing module 5, students will be able to: Identify the various components and functionality of Azure Sentinel. Identify use cases where Azure Sentinel would be a good solution. Describe Azure Sentinel workspace architecture Install Azure Sentinel workspace Manage an Azure Sentinel workspace Create a watchlist in Azure Sentinel Use KQL to access the watchlist in Azure Sentinel Manage threat indicators in Azure Sentinel Use KQL to access threat indicators in Azure Sentinel Module 6: Connect logs to Azure Sentinel Connect data at cloud scale across all users, devices, applications, and infrastructure, both on-premises and in multiple clouds to Azure Sentinel. The primary approach to connect log data is using the Azure Sentinel provided data connectors. This module provides an overview of the available data connectors. You will get to learn about the configuration options and data provided by Azure Sentinel connectors for Microsoft 365 Defender. Lessons M6 Connect data to Azure Sentinel using data connectors Connect Microsoft services to Azure Sentinel Connect Microsoft 365 Defender to Azure Sentinel Connect Windows hosts to Azure Sentinel Connect Common Event Format logs to Azure Sentinel Connect syslog data sources to Azure Sentinel Connect threat indicators to Azure Sentinel Lab M6: Connect logs to Azure Sentinel Connect Microsoft services to Azure Sentinel Connect Windows hosts to Azure Sentinel Connect Linux hosts to Azure Sentinel Connect Threat intelligence to Azure Sentinel After completing module 6, students will be able to: Explain the use of data connectors in Azure Sentinel Explain the Common Event Format and Syslog connector differences in Azure Sentinel Connect Microsoft service connectors Explain how connectors auto-create incidents in Azure Sentinel Activate the Microsoft 365 Defender connector in Azure Sentinel Connect Azure Windows Virtual Machines to Azure Sentinel Connect non-Azure Windows hosts to Azure Sentinel Configure Log Analytics agent to collect Sysmon events Explain the Common Event Format connector deployment options in Azure Sentinel Configure the TAXII connector in Azure Sentinel View threat indicators in Azure Sentinel Module 7: Create detections and perform investigations using Azure Sentinel Detect previously uncovered threats and rapidly remediate threats with built-in orchestration and automation in Azure Sentinel. You will learn how to create Azure Sentinel playbooks to respond to security threats. You'll investigate Azure Sentinel incident management, learn about Azure Sentinel events and entities, and discover ways to resolve incidents. You will also learn how to query, visualize, and monitor data in Azure Sentinel. Lessons M7 Threat detection with Azure Sentinel analytics Threat response with Azure Sentinel playbooks Security incident management in Azure Sentinel Use entity behavior analytics in Azure Sentinel Query, visualize, and monitor data in Azure Sentinel Lab M7: Create detections and perform investigations using Azure Sentinel Create Analytical Rules Model Attacks to Define Rule Logic Mitigate Attacks using Azure Sentinel Create Workbooks in Azure Sentinel After completing module 7, students will be able to: Explain the importance of Azure Sentinel Analytics. Create rules from templates. Manage rules with modifications. Explain Azure Sentinel SOAR capabilities. Create a playbook to automate an incident response. Investigate and manage incident resolution. Explain User and Entity Behavior Analytics in Azure Sentinel Explore entities in Azure Sentinel Visualize security data using Azure Sentinel Workbooks. Module 8: Perform threat hunting in Azure Sentinel In this module, you'll learn to proactively identify threat behaviors by using Azure Sentinel queries. You'll also learn to use bookmarks and livestream to hunt threats. You will also learn how to use notebooks in Azure Sentinel for advanced hunting. Lessons M8 Threat hunting with Azure Sentinel Hunt for threats using notebooks in Azure Sentinel Lab M8 : Threat hunting in Azure Sentinel Threat Hunting in Azure Sentinel Threat Hunting using Notebooks After completing this module, students will be able to: Describe threat hunting concepts for use with Azure Sentinel Define a threat hunting hypothesis for use in Azure Sentinel Use queries to hunt for threats. Observe threats over time with livestream. Explore API libraries for advanced threat hunting in Azure Sentinel Create and use notebooks in Azure Sentinel [-]

Vue.js, Vuex & Router Course [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: IT Introduksjon eller tilsvarende. Innleveringer: Øvinger: 8 må være godkjent.  Personlig veileder: ja Vurderingsform: Skriftlig eksamen, 3 timer Ansvarlig: Tore Mallaug Eksamensdato: 09.12.13 / 08.05.14         Læremål: Etter å ha gjennomført emnet skal studenten ha følgende samlede læringsutbytte: KUNNSKAPER:Kandidaten skal:- kjenne sentrale begreper innen databaser og datamodellering, og kan gjøre rede for disse- forstå hvordan en relasjonsdatabase er bygd opp ved å se på relasjonene (tabellene) og tilhørende nøkler- forstå (tolke) et (E)ER-diagram modellert i fagets gjeldende notasjon, og vite hvordan dette kan oversettes til relasjonsmodellen- gjøre rede for hvordan databaser kan fungere i en klient/tjener-arkitektur. FERDIGHETER:Kandidaten skal kunne:- tegne sitt eget (E)ER-diagram for å oppnå en god databasestruktur- lage sin egen normaliserte relasjonsdatabase med nøkler og referanseintegritet, og opprette databasen i et valgt databaseverktøy (databasesystem)- utføre SQL-spørringer mot en gitt database- lage en relasjonsdatabase som støtter opp om funksjonaliteten til et gitt grafisk brukergrensesnitt GENERELL KOMPETANSEKandidaten- viser en bevisst holdning til strukturell lagring og representasjon av data i et informasjonssystem- viser en bevisst holdning til databasedesign for å unngå unødvendig dobbeltlagring av data i en database Innhold:Innføring i datamodellering med EER og UML-notasjon. Design av relasjonsdatabase inkl. bruk av nøkler, referanseintegritet og enkel normalisering. Databasedefinisjon (DDL) og datamanipulering (DML) i SQL. Bruk av et valgt databaseverktøy (MySQL), se sammenhengen mellom datamodell, databaseverktøy og applikasjon / web-grensesnitt (klient/tjener -arkitektur).Les mer om faget herDemo: Her er en introduksjonsvideo for faget Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Databaser 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.  [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Grunnleggende objektorientert programmering i for eksempel Java eller C++ Innleveringer: Øvinger: 8 av 11 må være godkjent.  Personlig veileder: ja Vurderingsform: Skriftlig eksamen, 4 timer. Case-beskrivelser etc. legges ut i ItsLearning 24 timer før. (NB! Eksamensform kan bli endret under forutsetning av at ny teknologi gjør det mulig å arrangere eksamen elektronisk.) Ansvarlig: Grethe Sandstrak Eksamensdato: 05.12.13 / 08.05.14         Læremål: Etter å ha gjennomført emnet skal kandidaten ha følgende samlete læringsutbytte: KUNNSKAPER:Kandidaten:- kan gjøre rede for sentrale begreper innen objektorientering- kan konstruere et objektorientert C#. NET-program ut fra en gitt problemstilling- kan finne fram, sette seg inn i og anvende dokumentasjon om .NET Framework library- kjenner til ulike GUI-komponenter og hvordan de brukes i C#-programmer FERDIGHETER:Kandidaten kan:- sette opp programmiljø for å utvikle og kjøre C#. NET applikasjoner på egen pc- kan anvende klasser fra .NET Framework library- lage C#.NET program* med fordeling av oppgaver mellom objekter og der arv og polymorfi benyttes* med grafiske brukergrensesnitt* som kommuniserer med en database via SQL* med LINQ, delegater, templates GENERELL KOMPETANSEKandidaten kan:- kommunisere om objektorientert programmering og databaser med relevant begrepsapparat Innhold:NET-arkitekturen. Utviklingsmiljøet. Grunnleggende C#-syntaks. Objektorientert programmering med arv og polymorfi. GUI. Datafiler. Programmering mot databaser. ADO.NET, LINQ, Templates, Collections.Les mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag C#.NET 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

  COURSE OVERVIEW This course will provide foundational level knowledge of cloud services and how those services are provided with Microsoft Azure. The course can be taken as an optional first step in learning about cloud services and Microsoft Azure, before taking further Microsoft Azure or Microsoft cloud services courses. The course will cover general cloud computing concepts as well as general cloud computing models and services such as Public, Private and Hybrid cloud and Infrastructure-as-a-Service (IaaS), Platform-as-a-Service(PaaS) and Software-as-a-Service (SaaS). It will also cover some core Azure services and solutions, as well as key Azure pillar services concerning security, privacy, compliance and trust. It will finally cover pricing and support services available with Azure.   COURSE CONTENT  Module 1: Cloud Concepts -Learning Objectives-Why Cloud Services?-Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS)-Public, Private, and Hybrid cloud models Module 2: Core Azure Services -Core Azure architectural components-Core Azure Services and Products-Azure Solutions-Azure management tools Module 3: Security, Privacy, Compliance and Trust -Securing network connectivity in Azure-Core Azure Identity services-Security tools and features-Azure governance methodologies-Monitoring and Reporting in Azure-Privacy, Compliance and Data Protection standards in Azure Module 4: Azure Pricing and Support -Azure subscriptions-Planning and managing costs-Support options available with Azure-Service lifecycle in Azure     This course helps to prepare for exam AZ-900. [-]