IT-kurs

Excel for Selgere - elæringskurs [-]

Modern Application Architecture [-]

 This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. TARGET AUDIENCE This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. COURSE CONTENT Module 1: Introduction to Azure Machine Learning In this module, you will learn how to provision an Azure Machine Learning workspace and use it to manage machine learning assets such as data, compute, model training code, logged metrics, and trained models. You will learn how to use the web-based Azure Machine Learning studio interface as well as the Azure Machine Learning SDK and developer tools like Visual Studio Code and Jupyter Notebooks to work with the assets in your workspace. Getting Started with Azure Machine Learning Azure Machine Learning Tools Lab : Creating an Azure Machine Learning WorkspaceLab : Working with Azure Machine Learning Tools After completing this module, you will be able to Provision an Azure Machine Learning workspace Use tools and code to work with Azure Machine Learning Module 2: No-Code Machine Learning with Designer This module introduces the Designer tool, a drag and drop interface for creating machine learning models without writing any code. You will learn how to create a training pipeline that encapsulates data preparation and model training, and then convert that training pipeline to an inference pipeline that can be used to predict values from new data, before finally deploying the inference pipeline as a service for client applications to consume. Training Models with Designer Publishing Models with Designer Lab : Creating a Training Pipeline with the Azure ML DesignerLab : Deploying a Service with the Azure ML Designer After completing this module, you will be able to Use designer to train a machine learning model Deploy a Designer pipeline as a service Module 3: Running Experiments and Training Models In this module, you will get started with experiments that encapsulate data processing and model training code, and use them to train machine learning models. Introduction to Experiments Training and Registering Models Lab : Running ExperimentsLab : Training and Registering Models After completing this module, you will be able to Run code-based experiments in an Azure Machine Learning workspace Train and register machine learning models Module 4: Working with Data Data is a fundamental element in any machine learning workload, so in this module, you will learn how to create and manage datastores and datasets in an Azure Machine Learning workspace, and how to use them in model training experiments. Working with Datastores Working with Datasets Lab : Working with DatastoresLab : Working with Datasets After completing this module, you will be able to Create and consume datastores Create and consume datasets Module 5: Compute Contexts One of the key benefits of the cloud is the ability to leverage compute resources on demand, and use them to scale machine learning processes to an extent that would be infeasible on your own hardware. In this module, you'll learn how to manage experiment environments that ensure consistent runtime consistency for experiments, and how to create and use compute targets for experiment runs. Working with Environments Working with Compute Targets Lab : Working with EnvironmentsLab : Working with Compute Targets After completing this module, you will be able to Create and use environments Create and use compute targets Module 6: Orchestrating Operations with Pipelines Now that you understand the basics of running workloads as experiments that leverage data assets and compute resources, it's time to learn how to orchestrate these workloads as pipelines of connected steps. Pipelines are key to implementing an effective Machine Learning Operationalization (ML Ops) solution in Azure, so you'll explore how to define and run them in this module. Introduction to Pipelines Publishing and Running Pipelines Lab : Creating a PipelineLab : Publishing a Pipeline After completing this module, you will be able to Create pipelines to automate machine learning workflows Publish and run pipeline services Module 7: Deploying and Consuming Models Models are designed to help decision making through predictions, so they're only useful when deployed and available for an application to consume. In this module learn how to deploy models for real-time inferencing, and for batch inferencing. Real-time Inferencing Batch Inferencing Lab : Creating a Real-time Inferencing ServiceLab : Creating a Batch Inferencing Service After completing this module, you will be able to Publish a model as a real-time inference service Publish a model as a batch inference service Module 8: Training Optimal Models By this stage of the course, you've learned the end-to-end process for training, deploying, and consuming machine learning models; but how do you ensure your model produces the best predictive outputs for your data? In this module, you'll explore how you can use hyperparameter tuning and automated machine learning to take advantage of cloud-scale compute and find the best model for your data. Hyperparameter Tuning Automated Machine Learning Lab : Tuning HyperparametersLab : Using Automated Machine Learning After completing this module, you will be able to Optimize hyperparameters for model training Use automated machine learning to find the optimal model for your data Module 9: Interpreting Models Many of the decisions made by organizations and automated systems today are based on predictions made by machine learning models. It's increasingly important to be able to understand the factors that influence the predictions made by a model, and to be able to determine any unintended biases in the model's behavior. This module describes how you can interpret models to explain how feature importance determines their predictions. Introduction to Model Interpretation using Model Explainers Lab : Reviewing Automated Machine Learning ExplanationsLab : Interpreting Models After completing this module, you will be able to Generate model explanations with automated machine learning Use explainers to interpret machine learning models Module 10: Monitoring Models After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes techniques for monitoring models and their data. Monitoring Models with Application Insights Monitoring Data Drift Lab : Monitoring a Model with Application InsightsLab : Monitoring Data Drift After completing this module, you will be able to Use Application Insights to monitor a published model Monitor data drift   [-]

COURSE OVERVIEW TOGAF® V9.2  is the foremost generic framework in the field of Enterprise Architecture (EA). This course provides guidance on what to do to establish an architecture practice and how to use it in connection with planning the longer-term transformation of the enterprise (strategic architecture), and designing capabilities to support and sustain the transformation. This course will benefit: Practicing architects from complex organizations looking for a set of defined processes to help in the organization, governance and management of architecture teams and multiple architecture projects. Experienced architects looking for details on the elements of sound architectural process and practice. Senior managers, such as Project Managers and Service Managers, who wish to gain a full appreciation of architecture practice. Aspiring architects commencing their career wishing to obtain recognized EA certification. This TOGAF® accredited course examines how practitioners can base their activities on a set of well-defined processes. It examines the framework as a whole, including the numerous techniques to assist in organizing, governing and now in this version, describing, architecture. It incorporates recommendations on how to adapt the framework to deal with issues such as Security and Service-oriented Architecture. The course prepares participants to take the combined TOGAF® 9.2 Foundation and Certified exams (Level 1 & 2). During the course, delegates will be helped to prepare for this combined exam. This TOGAF® for Practitioners Level 1&2 course is being run by Global Knowledge and is accredited by The Open Group. For full details of the TOGAF® certification scheme, visit the following link: www.opengroup.org COURSE OBJECTIVES This workshop has been designed to enable participants to: Understand the basic concepts of enterprise architecture and TOGAF® Explain the features of TOGAF® and its methodology Implement TOGAF® in their work to maximum effect Develop an understanding of the necessary body of knowledge to achieve certification by examination for TOGAF® COURSE CONTENT Day 1 Introduction TOGAF® Basic / Core Concepts Introduction to the ADM Enterprise Continuum ADM Phases ADM Guidelines Architecture Governance Daily Wrap up / Q&A Day Two Architecture Views, Viewpoints, and Stakeholders Building Blocks ADM Deliverables TOGAF® Reference Models Preliminary Phase The Architecture Governance Framework Architecture Content Framework TOGAF® Content Metamodel Stakeholder Management Architecture Implementation Techniques Daily Wrap up / Q&A Day Three Phase A: Architecture Business Scenarios Technique Phase B: Business Architecture Phase C: Information Systems Architectures – Data Architecture Phase C: Information Systems Architectures – Application Architecture TOGAF®Foundation Architecture: Technical Reference Model Integrated Information Infrastructure Reference Model Phase D: Technology Architecture Daily Wrap up / Q&A Day Four Phase E: Opportunities and Solutions Migration Planning Techniques Phase F: Migration Planning Phase G: Implementation Governance Phase H: Architecture Change Management ADM Requirements Management Architecture Partitioning Guidelines for Adapting the ADM: Iteration and Levels Guidelines for Adapting the ADM: Security Guidelines for Adapting the ADM: SOA Architecture Maturity Models Architecture Skills Framework Daily Wrap up / Q&A TEST CERTIFICATION Once you have completed the course and are ready to book your exam at a Test Centre, please contact Global Knowledge and we will email your exam voucher code so that you can redeem it.  Exams can also be sat online https://www.opengroup.org/certifications/online-proctored-exams Achieving this level of Certification also qualifies delegates to take the BCS Practitioner Certificate in Enterprise and Solution Architecture without the need for the BCS Intermediate Certificate. [-]

Lær å lage nettsider med WordPress Dette kurset passer for deg som skal designe eller bruke nettsider laget med WordPress og som trenger å forstå hvordan det virker. Du lærer også hvordan du forandrer og tilpasser designmaler, bruker utvidelser, knytter nettsiden mot sosiale medier, og hvordan du søkemotoroptimaliserer nettsidene slik at du blir funnet av brukerene. WordPress er en publiseringsløsning som gjør det enkelt å lage profesjonelle nettsider og det har den fordelen at kunden kan oppdatere og legge inn eget innhold. Dette er verdens største publiseringsverktøy og det finnes utallige designmaler som gjør det mulig for deg å endre utseende på nettsiden uten å endre innholdet. Dette lærer du: Bli kjent med løsningen Opprette nettsider på eget domene Du lærer å lage nettsider ved hjelp av ferdige maler Endre designmaler Publisere nettsider og innlegg Legge inn bilder Gjøre nettsiden din søkbar Bruk av plugins og widgets slik som f. eks: deling i sosiale medier, slideshow, kalenderfunksjon og mye mer Enkel bilde­redigering i WordPress https://igm.no/wordpress-kurs/ [-]

SAFe® Scrum Master Certification [-]

Bli sertifisert i beste praksis innen porteføljestyring av prosjekter og programmer!Ønsker du å lære hvordan du sikrer en optimal prioritering av virksomhetens investeringer slik at de bidrar til å nå virksomhetens strategiske mål? Da trenger du gode verktøy og teknikker for å identifisere og prioritere blant ulike prosjekter samt å få god oversikt over alle ønskede gevinster. Det får du på dette kurset! MoP® gir deg rammeverket for å definere og gjennomføre endringsinitiativer gjennom effektiv porteføljestyring. Vi arrangerer sertifiseringskurset med svært dyktig instruktør. Undervisningen foregår på norsk og det benyttes norsk  begrepsapparat.   Læringsutbytte I kurset vil du vil bli godt kjent med prinsipper, teknikker og internasjonalt anerkjent beste praksis knyttet til organisering, utvelgelse og prioritering av investeringer i en portefølje. Du vil lære å investere i de riktige prosjektene og programmene, å kunne avslutte prosjekter som ikke er lønnsomme, samt å utnytte muligheter og håndtere risiko på en effektiv måte.  Innhold i kurset MoP® Foundation kurset inneholder følgende elementer: •  Introduksjon til MoP® •  5 fleksible prinsipper•  2 sykluser•  12 porteføljestyringspraksiser•  MoP®-sertifisering/eksamen siste kursdag For mer informasjon, besøk Axelos sine sider Kursdetaljer og forberedelser MoP® Foundation kurset går over 3 dager. I etterkant av kurset gjennomfører du en online eksamen. Pensumbok og eksamen er på engelsk, men undervisningen i kurset er på norsk. Kursholder kobler sammen de engelske og norske begrepene i kurset. Papirbasert eksamen Eksamen gjennomføres i klasserommet - på papir (multiple choice), siste kursdag. Det er også mulig å gjennomføre eksamen online fra din PC, i etterkant av kurset og innen 12 måneder. Merk at du må ha kamera på maskinen din. I så tilfelle må du gi oss beskjed ved oppstart av kurset. Kursholder vil også informere om eksamen i starten av kurset. Eksamen • 40 minutter• 50 multiple choice spørsmål• 50 % riktig besvart = bestått sertifisering• Hjelpemidler er ikke tiltatt• Eksamen er på engelsk Pensum (engelsk) Digital pensumbok (MoP® manualen “Management of Portfolios”) er inkludert i prisen. Du får tilgang til denne via PeopleCert sin kandidatportal PASSPORT. Denne bør gjennomgås i sin helhet i forkant av kurset og inngår som en del av eksamensforberedelsene. Holte Academy er akkreditert treningsorganisasjon for MoP®. MoP® is a registered trademark of the PeopleCert group. Used under licence from PeopleCert. All rights reserved. [-]

AZ-104: Microsoft Azure Administrator [-]

Bli en ekspert i online annonsering med Google Ads gjennom dette dyptgående kurset ledet av Espen Faugstad, gründer av Utdannet.no og en veteran med over 10 års erfaring i digital markedsføring. Dette kurset er skreddersydd for alle, fra de som aldri har brukt Google Ads før, til de som har erfaring men ønsker å heve sin kompetanse til ekspertnivå. Kurset starter med grunnleggende om hvordan du oppretter og konfigurerer en Google Ads-konto. Du vil lære å installere Google Ads-taggen og konverteringssporing, utføre målgruppe- og søkeordsanalyse, og forstå hvordan Google Ads-auksjonen fungerer. Kurset dekker også hvordan du oppretter og optimaliserer ulike typer annonser, inkludert tekst-, bilde-, video- og remarketingannonser. Med en praktisk tilnærming vil kurset guide deg gjennom prosessen med å sette opp effektive kampanjer, forstå auksjonssystemet, og bruke analyseverktøy for å forbedre dine resultater. Ved kursets slutt vil du ha tilegnet deg den kunnskapen du trenger for å mestre Google Ads og drive effektiv annonsering på vegne av deg selv eller dine klienter.   Innhold: Kapittel 1: Introduksjon Kapittel 2: Målgruppe Kapittel 3: Søkeord Kapittel 4: Auksjon Kapittel 5: Tekstannonser Kapittel 6: Bildeannonser Kapittel 7: Videoannonser Kapittel 8: Remarketing Kapittel 9: Analyse Kapittel 10: Avslutning   Varighet: 5 timer og 12 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. [-]

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 lære å jobbe raskere, smartere og bedre ved å ta i bruk OneNote.   Kursinnhold:   Lage notater Skriving av notater Bruk av koder for å raskt finne igjen informasjon Bruk av formler Disponere notatsidene Bruk av Outlook-oppgave og automatisk lage koblinger til oppgaver, kontakter og avtaler i Outlook.   Flere notatvarianter Ta opp og spille av lydnotater man kan søke i Lage tegninger og håndtere bilder, fange skjermutklipp og tekstgjenkjenning i bilder Jobbe med håndskrevne notater   Gjennomgå og organisere notater Organisere notatene i notatblokker, inndelinger, sider og undersider Søk etter notater Rapport på koder   Deling av notater med andre brukere Lage en delt notatblokk Passordbeskytte notater Bruk av OneDrive   Tilpasse OneNote   Bruk av OneNote med andre Office-programmer Forankre OneNote til skrivebordet Koblede notater Skrive ut til OneNote   Oppfølging av notater i Outlook   Møtenotater fra Outlook     4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti [-]

Architecting on AWS [-]

I dagens digitaliserte verden øker mengden data med enorme størrelser hver eneste dag. Enten man jobber i store multinasjonale selskap eller i små bedrifter ser man behovet for å dykke ned i data for å skaffe bedre innsikt. Veien dit vil variere fra sted til sted, men en fellesnevner er å bygge opp kompetanse rundt virksomheten sine data. Selvbetjening er en viktig bidragsyter for å bygge kompetansen og bli mer datadrevet. Begrepet kan defineres som en enkel form av styringsinformasjonssystemet, hvor brukeren har tilgang til relevant data og genererer rapporter og/eller analyser med hjelp av selvbetjeningsverktøy. Formålet er gi brukeren mulighet til å optimalisere og forenkle sine arbeidsoppgaver i tillegg til å frigjøre IT spesialister. Power BI er et verktøy som kan hjelpe dere på veien til å bli mer selvbetjent. Det er et kraftfullt analyse– og modelleringsverktøy som gjør at man kan kombinere data fra ulike kilder og sammenstille dem i rapporter og dashboards. Disse kan enkelt deles med andre i organisasjonen og tilgangsstyres i henhold til GDPR, personvern og teknisk kompetanse. Dette kurset gir en grunnleggende innføring i bruk av Power BI Desktop som selvbetjenings- og analyseverktøy for controllere, analytikere og de som jobber med virksomhetsrapportering. Deltakerne vil få en grunnleggende innføring i: Innlasting av data Datamodellering (best practice) Forhold mellom tabeller Power Query og datatransformasjoner DAX (kalkulerte mål og kolonner) Datavisualisering, formattering og rapportoppsett Filtrering, slicers og drillthrough funksjon Navigasjon og bokmerker Publisering av rapport til Power BI Service og overordnet modell for utrulling av Power BI i organisasjonen vil bli presentert i kurset, men disse tema vil ikke bli dekket i dybden. Ta med egen PC med nyeste versjon av Power BI. Du bør også ha signet opp med en 30-dagers gratislisens for Power BI Pro.   Kursinnhold Innlastning av data Kurset bygger på et datasett fra en fiktiv global leverandør av sykkelutstyr hvor data er fordelt på en fakta tabell med tilhørende dimensjonstabeller. Datasettet hentes fra en Excel-fil som er tilsendt før kurset, men denne fremgangsmåten kan enkelt overføres til andre strukturerte databaser. Datamodellering Når vi bruker data fra flere tabeller er det viktig å definere en datamodell som muliggjør analyser på tvers av tabellene. Dette kurset gjennomgår grunnleggende teori om datamodellering sammen med en praktisk gjennomgang av hvordan man oppretter relasjoner og bygger en datamodell i Power BI. Bruke Power Query til å transformere data Power Query er et utrolig kraftig verktøy til å skreddersy data før de lastes inn i Power BI (ETL). Dette kurset gjør deltakerne kjent med hvordan Power BI og Power Query samhandler, og det blir demonstrert enkelte funksjoner i Power Query. Herunder rydding i data via navngivning, sletting og formattering av kolonner. Opprettelsen av en betinget kolonne blir også gjennomgått i kurset. DAX (Kalkulerte mål og kolonner) DAX er språket som brukes til å utføre spesifikke kalkulasjoner på data i Power BI. Dette er et språk hvor man kan utføre ganske komplekse utregninger, og kurset gir en introduksjon til dette på et nybegynnernivå. Det vil si at vi i kurset utarbeider mål og kolonner ved bruk av funksjoner som SUM, COUNT og CALCULATE. Datavisualisering, formattering og rapport oppsett Kurset gjennomgår flere av de vanlige visualiseringstypene som søylediagram, hjuldiagram og tabeller, og det blir vist formateringsmuligheter som valg av farge, kantlinje og akseformattering. Kurset legger også vekt på samhandling mellom visualiseringene, og det opprettes en interaktiv rapport med filtreringsvalg, ikoner og egendefinerte overskrifter. Navigasjon og bokmerker Kurset vil gjennomgå måter å navigere i rapporten på, samt den populære funksjonaliteten bookmarks som kan brukes til blant annet navigasjon og fjerning av anvendte filtre for å gjøre brukeropplevelsen av rapporten bedre.      [-]

AZ-500: Microsoft Azure Security Technologies [-]

The course is designed for Azure system administrators, solutions architects, and SysOps administrators who are familiar with Azure features and setup and want to gain experience configuring Google Cloud products immediately.  This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud. Objectives This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto-scaling, load balancing, storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introducing Google Cloud -Explain the advantages of Google Cloud-Define the components of Google’s network infrastructure, including points of presence, data centers, regions, and zones-Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Module 2: Getting Started with Google Cloud -Identify the purpose of projects on Google Cloud-Understand how Azure’s resource hierarchy differs from Google Cloud’s-Understand the purpose of and use cases for Identity and Access Management-Understand how Azure AD differs from Google Cloud IAM-List the methods of interacting with Google Cloud-Launch a solution using Cloud Marketplace Module 3: Virtual Machines in the Cloud -Identify the purpose and use cases for Google Compute Engine-Understand the basics of networking in Google Cloud-Understand how Azure VPC differs from Google VPC-Understand the similarities and differences between Azure VM and Google Compute Engine-Understand how typical approaches to load-balancing in Google Cloud differ from those in AzureDeploy applications using Google Compute Engine Module 4: Storage in the Cloud -Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore-Understand how Azure Blob compares to Cloud Storage-Compare Google Cloud’s managed database services with Azure SQL-Learn how to choose among the various storage options on Google Cloud-Load data from Cloud Storage into BigQuery Module 5: Containers in the Cloud -Define the concept of a container and identify uses for containers-Identify the purpose of and use cases for Google Container Engine and Kubernetes-Understand how Azure Kubernetes Service differs from Google Kubernetes Engine-Provision a Kubernetes cluster using Kubernetes Engine-Deploy and manage Docker containers using kubectl Module 6: Applications in the Cloud -Understand the purpose of and use cases for Google App Engine-Contrast the App Engine Standard environment with the App Engine Flexible environment-Understand how App Engine differs from Azure App Service-Understand the purpose of and use cases for Google Cloud Endpoints Module 7: Developing, Deploying and Monitoring in the Cloud -Understand options for software developers to host their source code-Understand the purpose of template-based creation and management of resources-Understand how Cloud Deployment Manager differs from Azure Resource Manager-Understand the purpose of integrated monitoring, alerting, and debugging-Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics-Create a Deployment Manager deployment-Update a Deployment Manager deployment-View the load on a VM instance using Google Monitoring Module 8: Big Data and Machine Learning in the Cloud -Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms-Understand how Google Cloud BigQuery differs from Azure Data Lake-Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus-Understand how Google Cloud’s machine-learning APIs differ from Azure’s-Load data into BigQuery from Cloud Storage-Perform queries using BigQuery to gain insight into data Module 9: Summary and Review -Review the products that make up Google Cloud and remember how to choose among them-Understand next steps for training and certification-Understand, at a high level, the process of migrating from Azure to Google Cloud [-]

COURSE OVERVIEW  Through a combination of lecture and hands-on labs, you will learn how to install, operate, configure, and verify a basic IPv4 and IPv6 network. The course covers configuring network components such as switches, routers, and Wireless LAN Controllers; managing network devices; and identifying basic security threats. Network programmability, automation, and software-defined networking are also covered at a foundational level.   This course helps you prepare to take the 200-301 Cisco Certified Network Associate (CCNA) exam.   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 recieve at the beginning of the course and should be part of your preparation for the exam. Lab access is provided for both the class and the self- study sections, lab access is valid for 60 hours or 90 days whichever is the shorter, so please ensure you exit the lab exercises when not in use. TARGET AUDIENCE Anyone looking to start a career in networking or wishing to achieve the Cisco CCNA Certification. COURSE OBJECTIVES After completing this course you should be able to: Identify the components of a computer network and describe their basic characteristics Understand the model of host-to-host communication Describe the features and functions of the Cisco IOS Software Describe LANs and the role of switches within LANs Describe Ethernet as the network access layer of TCP/IP and describe the operation of switches Install a switch and perform the initial configuration Describe the TCP/IP internet Layer, IPv4, its addressing scheme, and subnetting Describe the TCP/IP Transport layer and Application layer Explore functions of routing Implement basic configuration on a Cisco router Explain host-to-host communications across switches and routers Identify and resolve common switched network issues and common problems associated with IPv4 addressing Describe IPv6 main features, addresses and configure and verify basic IPv6 connectivity Describe the operation, benefits, and limitations of static routing Describe, implement and verify VLANs and trunks Describe the application and configuration of inter-VLAN routing Explain the basics of dynamic routing protocols and describe components and terms of OSPF Explain how STP and RSTP work Configure link aggregation using EtherChannel Describe the purpose of Layer 3 redundancy protocols Describe basic WAN and VPN concepts Describe the operation of ACLs and their applications in the network Configure internet access using DHCP clients and explain and configure NAT on Cisco routers Describe the basic QoS concepts Describe the concepts of wireless networks, which types of wireless networks can be built and how to use WLC Describe network and device architectures and introduce virtualization Introduce the concept of network programmability and SDN and describe the smart network management solutions like Cisco DNA Center, SD-Access and SD-WAN Configure basic IOS system monitoring tools Describe the management of Cisco devices Describe the current security threat landscape Describe threat defense technologies Implement a basic security configuration of the device management plane Implement basic steps to harden network devices COURSE CONTENT Exploring the Functions of Networking Introducing the Host-To-Host Communications Model Operating Cisco IOS Software Introducing LANs Exploring the TCP/IP Link Layer Starting a Switch Introducing the TCP/IP Internet Layer, IPv4 Addressing, and Subnets Explaining the TCP/IP Transport Layer and Application Layer Exploring the Functions of Routing Configuring a Cisco Router Exploring the Packet Delivery Process Troubleshooting a Simple Network Introducing Basic IPv6 Configuring Static Routing Implementing VLANs and Trunks Routing Between VLANs Introducing OSPF Building Redundant Switched Topologies (Self-Study) Improving Redundant Switched Topologies with EtherChannel Exploring Layer 3 Redundancy (Self-Study) Introducing WAN Technologies (Self-Study) Explaining Basics of ACL Enabling Internet Connectivity Introducing QoS (Self-Study) Explaining Wireless Fundamentals (Self-Study) Introducing Architectures and Virtualization (Self-Study) Explaining the Evolution of Intelligent Networks Introducing System Monitoring Managing Cisco Devices Examining the Security Threat Landscape (Self-Study) Implementing Threat Defense Technologies (Self-Study) Securing Administrative Access Implementing Device Hardening Labs: Get Started with Cisco CLI Observe How a Switch Operates Perform Basic Switch Configuration Inspect TCP/IP Applications Configure an Interface on a Cisco Router Configure and Verify Layer 2 Discovery Protocols Configure Default Gateway Explore Packet Forwarding Troubleshoot Switch Media and Port Issues Troubleshoot Port Duplex Issues Configure Basic IPv6 Connectivity Configure and Verify IPv4 Static Routes Configure IPv6 Static Routes Configure VLAN and Trunk Configure a Router on a Stick Configure and Verify Single-Area OSPF Configure and Verify EtherChannel Configure and Verify IPv4 ACLs Configure a Provider-Assigned IPv4 Address Configure Static NAT Configure Dynamic NAT and PAT Log into the WLC Monitor the WLC Configure a Dynamic (VLAN) Interface Configure a DHCP Scope Configure a WLAN Define a RADIUS Server Explore Management Options Explore the Cisco DNA Center Configure and Verify NTP Create the Cisco IOS Image Backup Upgrade Cisco IOS Image Configure WLAN Using WPA2 PSK Using the GUI Secure Console and Remote Access Enable and Limit Remote Access Connectivity Secure Device Administrative Access Configure and Verify Port Security Implement Device Hardening TEST CERTIFICATION Recommended as preparation for the following exams:  200-301 -  Cisco Certified Network Associate Exam (CCNA) [-]