Oversikt over relevante kurs innen Kurs i programvare og applikasjoner i Hommersåk

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

Sammenligne tegninger, også i batch Hvordan standardisere designgjennomgangen? Opprette tilpassede markeringsverktøy i Tool Chest Bruk av Markeringslisten for sporing, kommentering og status på markeringer Samhandling i sanntid mellom forskjellige aktører under designgjennomgangen i Studio Sessions [-]

Dette er et spesialkurs som fokuserer på analyse av store datasett ved hjelp av Pivottabell og Power Pivot, samt formelbasert analyse. Målet er å få frem styrker og svakheter ved de forskjellige metodene, og å se litt på hvilke forutsetninger som påvirker valg av løsning. For å ha utbytte av dette kurser forutsettes at man er vant bruker av Excel. Pivot og Power Pivot blir gjennomgått fra begynnelsen, så man trenger ikke være kjent med disse verktøyene fra før. Betingede formler kan være ganske krevende, så det er en fordel å være litt trygg på formelskriving. I en kurssituasjon blir selvsagt kurset tilpasset deltagernes nivå og forkunnskaper. I kurset gjennomgås bl.a.: Kontroll/gjennomgang av en del sentral funksjonalitet – bl.a. absolutte, relative og blandede referanser. Sammendrag av data fra flere ark i samme eller flere arbeidsbøker, bl.a. gjennomgående summering og tabulering v.hj.a. INDIREKTE-funksjonen. Betingende sammendrag v.hj.a. matriseformler og funksjoner Modifisere datasett med FINN.RAD, FINN.KOLONNE, matriseformler og andre teknikker Pivottabell, hvor vi bl.a. ser på: Sette sammen data fra forskjellige grunnlag før pivotering Vise dataserie på forskjellige måter (sum, gjennomsnitt, prosentfordelt, etc.) Hvordan foreta beregninger rett i pivottabellen, f.ex. inntekter – kostnader = resultat Pivottabell hvor datagrunnlaget er oppdelt i flere forskjellige Pivottabell rett mot en spørring i en database Power Pivot Forskjeller (og likheter) med «vanlig» Pivottabell Når forlater vi den vanlige pivottabellen til fordel for Power Pivot? Fordeler og ulemper med Pivot og Power Pivot. Lage Power Pivot-tabell med data fra flere forskjellige datasett. [-]

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 In this course, you will master the skills and technologies you need to implement core Cisco security solutions to provide advanced threat protection against cybersecurity attacks. You will learn security for networks, cloud and content, endpoint protection, secure network access, visibility and enforcements. You will get extensive hands-on experience deploying Cisco Firepower Next-Generation Firewall and Cisco ASA Firewall; configuring access control policies, mail policies, and 802.1X Authentication; and more.  You will get introductory practice on Cisco Stealthwatch Enterprise and Cisco Stealthwatch Cloud threat detection features. Please note that this course is a combination of Instructor-Led and Self-Paced Study - 5 days in the classroom and approx 3 days of self study. The self-study content will be provided as part of the digital courseware that you will recieve at the beginning of the course and should be part of your preparation for the exam. TARGET AUDIENCE Security individuals who need to be able to implement and operate core security technologies including network security, cloud security, content security, endpoint protection and detection, secure network access, visibility and enforcements. COURSE OBJECTIVES After completing this course you should be able to: Describe information security concepts and strategies within the network Describe common TCP/IP, network application, and endpoint attacks Describe how various network security technologies work together to guard against attacks Implement access control on Cisco ASA appliance and Cisco Firepower Next-Generation Firewall Describe and implement basic email content security features and functions provided by Cisco Email Security Appliance Describe and implement web content security features and functions provided by Cisco Web Security Appliance Describe Cisco Umbrella security capabilities, deployment models, policy management, and Investigate console Introduce VPNs and describe cryptography solutions and algorithms Describe Cisco secure site-to-site connectivity solutions and explain how to deploy Cisco IOS VTI-based point-to-point IPsec VPNs, and point-to-point IPsec VPN on the Cisco ASA and Cisco FirePower NGFW Describe and deploy Cisco secure remote access connectivity solutions and describe how to configure 802.1X and EAP authentication Provide basic understanding of endpoint security and describe AMP for Endpoints architecture and basic features Examine various defenses on Cisco devices that protect the control and management plane Configure and verify Cisco IOS Software Layer 2 and Layer 3 Data Plane Controls Describe Cisco Stealthwatch Enterprise and Stealthwatch Cloud solutions Describe basics of cloud computing and common cloud attacks and how to secure cloud environment   COURSE CONTENT Describing Information Security Concepts (Self-Study) Information Security Overview Managing Risk Vulnerability Assessment Understanding CVSS Describing Common TCP/IP Attacks (Self-Study) Legacy TCP/IP Vulnerabilities IP Vulnerabilities ICMP Vulnerabilities TCP Vulnerabilities UDP Vulnerabilities Attack Surface and Attack Vectors Reconnaissance Attacks Access Attacks Man-In-The-Middle Attacks Denial of Service and Distributed Denial of Service Attacks Reflection and Amplification Attacks Spoofing Attacks DHCP Attacks Describing Common Network Application Attacks (Self-Study) Password Attacks DNS-Based Attacks DNS Tunneling Web-Based Attacks HTTP 302 Cushioning Command Injections SQL Injections Cross-Site Scripting and Request Forgery Email-Based Attacks Describing Common Endpoint Attacks (Self-Study) Buffer Overflow Malware Reconnaissance Attack Gaining Access and Control Gaining Access via Social Engineering Gaining Access via Web-Based Attacks Exploit Kits and Rootkits Privilege Escalation Post-Exploitation Phase Angler Exploit Kit Describing Network Security Technologies Defense-in-Depth Strategy Defending Across the Attack Continuum Network Segmentation and Virtualization Overview Stateful Firewall Overview Security Intelligence Overview Threat Information Standardization Network-Based Malware Protection Overview IPS Overview Next Generation Firewall Overview Email Content Security Overview Web Content Security Overview Threat Analytic Systems Overview DNS Security Overview Authentication, Authorization, and Accounting Overview Identity and Access Management Overview Virtual Private Network Technology Overview Network Security Device Form Factors Overview Deploying Cisco ASA Firewall Cisco ASA Deployment Types Cisco ASA Interface Security Levels Cisco ASA Objects and Object Groups Network Address Translation Cisco ASA Interface ACLs Cisco ASA Global ACLs Cisco ASA Advanced Access Policies Cisco ASA High Availability Overview Deploying Cisco Firepower Next-Generation Firewall Cisco Firepower NGFW Deployments Cisco Firepower NGFW Packet Processing and Policies Cisco Firepower NGFW Objects Cisco Firepower NGFW NAT Cisco Firepower NGFW Prefilter Policies Cisco Firepower NGFW Access Control Policies Cisco Firepower NGFW Security Intelligence Cisco Firepower NGFW Discovery Policies Cisco Firepower NGFW IPS Policies Cisco Firepower NGFW Malware and File Policies Deploying Email Content Security Cisco Email Content Security Overview SMTP Overview Email Pipeline Overview Public and Private Listeners Host Access Table Overview Recipient Access Table Overview Mail Policies Overview Protection Against Spam and Graymail Anti-virus and Anti-malware Protection Outbreak Filters Content Filters Data Loss Prevention Email Encryption Deploying Web Content Security Cisco WSA Overview Deployment Options Network Users Authentication HTTPS Traffic Decryption Access Policies and Identification Profiles Acceptable Use Controls Settings Anti-Malware Protection Deploying Cisco Umbrella (Self-Study) Cisco Umbrella Architecture Deploying Cisco Umbrella Cisco Umbrella Roaming Client Managing Cisco Umbrella Cisco Umbrella Investigate Overview Explaining VPN Technologies and Cryptography VPN Definition VPN Types Secure Communication and Cryptographic Services Keys in Cryptography Public Key Infrastructure Introducing Cisco Secure Site-to-Site VPN Solutions Site-to-Site VPN Topologies IPsec VPN Overview IPsec Static Crypto Maps IPsec Static Virtual Tunnel Interface Dynamic Multipoint VPN Cisco IOS FlexVPN Deploying Cisco IOS VTI-Based Point-to-Point Cisco IOS VTIs Static VTI Point-to-Point IPsec IKEv2 VPN Configuration Deploying Point-to-Point IPsec VPNs on the Cisco ASA and Cisco Firepower NGFW Point-to-Point VPNs on the Cisco ASA and Cisco Firepower NGFW Cisco ASA Point-to-Point VPN Configuration Cisco Firepower NGFW Point-to-Point VPN Configuration Introducing Cisco Secure Remote Access VPN Solutions Remote Access VPN Components Remote Access VPN Technologies SSL Overview Deploying Remote Access SSL VPNs on the Cisco ASA and Cisco Firepower NGFW Remote Access Configuration Concepts Connection Profiles Group Policies Cisco ASA Remote Access VPN Configuration Cisco Firepower NGFW Remote Access VPN Configuration Explaining Cisco Secure Network Access Solutions Cisco Secure Network Access Cisco Secure Network Access Components AAA Role in Cisco Secure Network Access Solution Cisco Identity Services Engine Cisco TrustSec Describing 802.1X Authentication 802.1X and EAP EAP Methods Role of RADIUS in 802.1X Communications RADIUS Change of Authorization Configuring 802.1X Authentication Cisco Catalyst Switch 802.1X Configuration Cisco WLC 802.1X Configuration Cisco ISE 802.1X Configuration Supplicant 802.1x Configuration Cisco Central Web Authentication Describing Endpoint Security Technologies (Self-Study) Host-Based Personal Firewall Host-Based Anti-Virus Host-Based Intrusion Prevention System Application Whitelists and Blacklists Host-Based Malware Protection Sandboxing Overview File Integrity Checking Deploying Cisco AMP for Endpoints (Self-study) Cisco AMP for Endpoints Architecture Cisco AMP for Endpoints Engines Retrospective Security with Cisco AMP Cisco AMP Device and File Trajectory Managing Cisco AMP for Endpoints Introducing Network Infrastructure Protection (Self-Study) Identifying Network Device Planes Control Plane Security Controls Management Plane Security Controls Network Telemetry Layer 2 Data Plane Security Controls Layer 3 Data Plane Security Controls Deploying Control Plane Security Controls (Self-Study) Infrastructure ACLs Control Plane Policing Control Plane Protection Routing Protocol Security Deploying Layer 2 Data Plane Security Controls (Self-Study) Overview of Layer 2 Data Plane Security Controls VLAN-Based Attacks Mitigation STP Attacks Mitigation Port Security Private VLANs DHCP Snooping ARP Inspection Storm Control MACsec Encryption Deploying Layer 3 Data Plane Security Controls (Self-Study) Infrastructure Antispoofing ACLs Unicast Reverse Path Forwarding IP Source Guard Labs Configure Network Settings And NAT On Cisco ASA Configure Cisco ASA Access Control Policies Configure Cisco Firepower NGFW NAT Configure Cisco Firepower NGFW Access Control Policy Configure Cisco Firepower NGFW Discovery and IPS Policy Configure Cisco NGFW Malware and File Policy Configure Listener, HAT, and RAT on Cisco ESA Configure Mail Policies Configure Proxy Services, Authentication, and HTTPS Decryption Enforce Acceptable Use Control and Malware Protection Examine the Umbrella Dashboard Examine Cisco Umbrella Investigate Explore DNS Ransomware Protection by Cisco Umbrella Configure Static VTI Point-to-Point IPsec IKEv2 Tunnel Configure Point-to-Point VPN between the Cisco ASA and Cisco Firepower NGFW Configure Remote Access VPN on the Cisco Firepower NGFW Explore Cisco AMP for Endpoints Perform Endpoint Analysis Using AMP for Endpoints Console Explore File Ransomware Protection by Cisco AMP for Endpoints Console Explore Cisco Stealthwatch Enterprise v6.9.3 Explore CTA in Stealthwatch Enterprise v7.0 Explore the Cisco Cloudlock Dashboard and User Security Explore Cisco Cloudlock Application and Data Security Explore Cisco Stealthwatch Cloud Explore Stealthwatch Cloud Alert Settings, Watchlists, and Sensors TEST CERTIFICATION Recommended as preparation for the following exams: 350-701 - Implementing and Operating Cisco Security Core Technologies (SCOR 350-701)   This is the core exam for the Cisco CCNP Security certification, in order to gain the CCNP Security certification you will also need to pass one of the concentration exams. 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Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Windows server 2008/2012 - god kjennskap om Windows server Innleveringer: Øvinger: 8 av må være godkjent. Personlig veileder: ja Vurderingsform: Eksamen blir arrangert som 2 dagers hjemmeeksamen (start kl 09.00 og innlevering kl 15.00 dagen etter). Hver student får tildelt et virtuelt område. Det skal også leveres en skriftelig begrunnelse for de valg som er foretatt. Hjemmeeksamen, individuell, 2 dager, 0 Ansvarlig: Stein Meisingseth Eksamensdato: 10.12.13 / 13.05.14         Læremål: KUNNSKAPER:Kandidaten:- har innsikt i drift av nettverk basert på Windows Server, programvaredistribusjon og kjenner til hvilke verktøy som kan brukes for administrasjon av virtuelle maskiner og nettverk- kan forklare systemer som kan benyttes til overvåkning og vedlikehold FERDIGHETER:Kandidaten kan:- installere og konfigurere System Center Configuration Manager 2012- automatisere manuelle operasjoner- sikre, oppdatere og overvåke IT-systemer GENERELL KOMPETANSE:Kandidaten har:- perspektiv og kompetanse i å velge riktige og tilpassete driftsløsninger- kompetanse i å formidle driftsterminologi, både muntlig og skriftlig Innhold:- Automatisering og sikring ved hjelp av System Center Cooperation Manager 2012 (SCCM 2012) - Applikasjonsutrulling - Operativ System utrulling - Klient tilstands-monitorering - Programvare oppdateringer - Sikkerhetsbeskyttelse vha Endpoint ProtectionLes mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Microsoft System Center i overvåkning og drift 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

AZ-1001: Deploy and manage containers using Azure Kubernetes Service [-]

Oppdag kraften i Microsoft Excel med "Excel: Grunnleggende", et detaljert kurs ledet av Espen Faugstad hos Utdannet.no. Microsoft Excel er et essensielt verktøy for dataanalyse og regnearkbehandling, brukt i en rekke yrker og bransjer. Dette kurset er skreddersydd for å gi deg en solid forståelse av Excel, gjør deg i stand til å bruke programmet effektivt og med selvtillit. Kurset starter med de grunnleggende aspektene av Excel, inkludert navigering i brukergrensesnittet, bruk av hurtigtilgang, båndet, formellinjen og statuslinjen. Du vil lære å legge til og håndtere data, bruke formler og funksjoner for ulike beregninger som summering, gjennomsnitt, maksimum, minimum og mer. I tillegg vil du utforske hvordan du formaterer celler og bruker diagrammer for å presentere data på en visuell og tiltalende måte. Kurset dekker også hvordan du effektivt kan arbeide med arbeidsark og eksportere data. Ved kursets slutt vil du ha en grundig forståelse av Excel og være i stand til å bruke dets mange funksjoner for å utføre en rekke oppgaver, fra enkle beregninger til kompleks dataanalyse.   Innhold: Kapittel 1: Brukergrensesnitt Kapittel 2: Legg til data Kapittel 3: Formler og funksjoner Kapittel 4: Formatere Kapittel 5: Diagrammer Kapittel 6: Arbeidsark Kapittel 7: Eksportere Kapittel 8: Avslutning   Varighet: 2 timer og 15 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Tjenesten fungerer på samme måte som strømmetjenester for musikk eller TV-serier. Våre kunder betaler en fast månedspris og får tilgang til alle kursene som er produsert så langt. Plattformen har hatt en god vekst de siste årene og kan skilte med 30.000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling moro, spennende og tilgjengelig for alle – og med oss har vi Innovasjon Norge og Forskningsrådet. [-]

Utforsk Adobe Bridge til fulle med kurset "Bridge: Komplett" ledet av Espen Faugstad hos Utdannet.no. Adobe Bridge er et kraftig verktøy for å importere, organisere og vise digitale bilder, og er en viktig del av Creative Cloud-pakken. Dette kurset er designet for alle som ønsker å lære Adobe Bridge fra grunnen av, og ingen forkunnskaper er nødvendig. Du vil lære hvordan du effektivt importerer og organiserer bilder, rangerer og presenterer dem. Kurset vil gi deg en dyp forståelse av hvordan forskjellige paneler i Bridge, som Content-panelet, Filter-panelet, Collections-panelet, og Metadata-panelet, fungerer i praksis. Gjennom kurset vil du få praktisk erfaring med å bruke Bridge for å forbedre din arbeidsflyt og bildehåndtering. Ved slutten av kurset vil du ha oppnådd en omfattende forståelse av Adobe Bridge, noe som gjør deg i stand til å bruke programmet effektivt, enten du jobber alene eller sammen med andre Adobe-programmer som Photoshop.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Grunnleggende Kapittel 3: Viderekommen Kapittel 4: Avslutning   Varighet: 1 time   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Tjenesten fungerer på samme måte som strømmetjenester for musikk eller TV-serier. Våre kunder betaler en fast månedspris og får tilgang til alle kursene som er produsert så langt. Plattformen har hatt en god vekst de siste årene og kan skilte med 30.000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling moro, spennende og tilgjengelig for alle – og med oss har vi Innovasjon Norge og Forskningsrådet. [-]

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

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 [-]

Developing on AWS [-]

Elæring Cisco U. Essentials [-]

Hvem passer kurset for? Deg som lager presentasjoner eller presenterer/markedsfører innhold på nett. Forhåndskunnskap: Kurset llustrator innføring eller tilsvarende kunnskap Dette lærer du: Teknikker til tegning av enkle figurer og former til bruk i illustrasjonen Bruk av tall i diagrammer Tilpasning av diagrammets utseende Fargebruk Teknikker for å hente inn nye idéer https://igm.no/infografikk/ [-]

COURSE OVERVIEW The Implementing and Configuring Cisco Identity Services Engine course shows you how to deploy and use Cisco Identity Services Engine (ISE) v2.4, an identity and access control policy platform that simplifies the delivery of consistent, highly secure access control across wired, wireless and VPN connections. This hands-on course provides you with the knowledge and skills required to implement and use Cisco ISE, including policy enforcement, profiling services, web authentication and guest access services, BYOD, endpoint compliance services, and TACACS+ device administration. Through expert instruction and hands-on practice, you will learn how to use Cisco ISE to gain visibility into what is happening in your network, streamline security policy management and contribute to operational efficiency.   Delegates will be expected to work in groups and share lab equipment, If you are attending virtually you may also be required to work in virtual breakout rooms. Extended hours may also be required to cover all of the content included in this class.   TARGET AUDIENCE Individuals involved in the deployment and maintenance of the Cisco ISE platform. COURSE OBJECTIVES After completing this course you should be able to: Describe Cisco ISE deployments, including core deployment components and how they interact to create a cohesive security architecture. Describe the advantages of such a deployment and how each Cisco ISE capability contributes to these advantages. Describe concepts and configure components related to 802.1X and MAC Authentication Bypass (MAB) authentication, identity management, and certificate services. Describe how Cisco ISE policy sets are used to implement authentication and authorization, and how to leverage this capability to meet the needs of your organization. Describe third-party network access devices (NADs), Cisco TrustSec®, and Easy Connect. Describe and configure web authentication, processes, operation, and guest services, including guest access components and various guest access scenarios. Describe and configure Cisco ISE profiling services, and understand how to monitor these services to enhance your situational awareness about network-connected endpoints. Describe best practices for deploying this profiler service in your specific environment. Describe BYOD challenges, solutions, processes, and portals. Configure a BYOD solution, and describe the relationship between BYOD processes and their related configuration components. Describe and configure various certificates related to a BYOD solution. Describe the value of the My Devices portal and how to configure this portal. Describe endpoint compliance, compliance components, posture agents, posture deployment and licensing, and the posture service in Cisco ISE. Describe and configure TACACS+ device administration using Cisco ISE, including command sets, profiles, and policy sets. Understand the role of TACACS+ within the authentication, authentication, and accounting (AAA) framework and the differences between the RADIUS and TACACS+ protocols. Migrate TACACS+ functionality from Cisco Secure Access Control System (ACS) to Cisco ISE, using a migration tool. COURSE CONTENT Introducing Cisco ISE Architecture and Deployment Using Cisco ISE as a Network Access Policy Engine Cisco ISE Use Cases Describing Cisco ISE Fucntions Cisco ISE Deployment Models Context Visibility Cisco ISE Policy Enforcement Using 802.1X for Wired and Wireless Access Using MAC Authentication Bypass for Wired and Wireless Access Introducing Identity Management Configuring Certificate Services Introducing Cisco ISE Policy Implementing Third-Party Network Access Device Support Introducing Cisco TrustSec TrustSec Configuration Easy Connect Web Authentication and Guest Services Introducing Web Access with Cisco ISE Introducing Guest Access Components Configuring Guest Access Services Configure Sponsor and Guest Portals Cisco ISE Profiler Introducing Cisco ISE Profiler Profiling Deployment and Best Practices Cisco ISE BYOD Introducing the Cisco ISE BYOD Process Describing BYOD Flow Configuring the My Devices Portal Configuring Certificates in BYOD Scenarios Cisco ISE Endpoint Compliance Services Introducing Endpoint Compliance Services Configuring Client Posture Services and Provisioning Working with Network Access Devices Cisco ISE TACACS+ Device Administration Configure TACACS+ Device Administration Guidelines and Best Practices Migrating from Cisco ACS to Cisco ISE Labs Lab 1: Access the SISE Lab and Install ISE 2.4 Lab 2 : Configure Initial Cisco ISE Setup, Gui Familiarization and System Certificate Usage  Lab 3: Integrate Cisco ISE with Active Directory Lab 4: Configure Cisco ISE Policy Lab 5: Configure Access Policy for Easy Connect Lab 6: Configure Guest Access Lab 7: Configure Guest Access Operations Lab 8: Create Guest Reports Lab 9: Configure Profiling Lab 10: Customize the Cisco ISE Profiling Configuration Lab 11: Create Cisco ISE Profiling Reports Lab 12: Configure BYOD Lab 13: Blacklisting a Device Lab 14: Configure Cisco ISE Compliance Services Lab 15: Configure Client Provisioning Lab 16: Configure Posture Policies Lab 17: Test and Monitor Compliance Based Access Lab 18: Test Compliance Policy Lab 19: Configure Cisco ISE for Basic Device Administration Lab 20: Configure TACACS+ Command Authorization   [-]