Oversikt over relevante kurs innen IT-kurs i Västerås kommune

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

Understand the key concepts of Relationship Management, Supplier Management, Service Level Management, Continual Improvement, and Information Security Management, elucidating their significance in fostering collaboration, ensuring service quality, driving continual improvement, and maintaining information security. This eLearning is: Interactive Self-paced   Device-friendly   12 hours content   Mobile-optimised   Practical exercises   Exam: 60 questions Multiple choise 90 minutes Closed book Minimum required score to pass: 65% [-]

Understand the purpose and key concepts of the Service Level Management Practice, elucidating its significance in defining, negotiating, and managing service levels to meet customer expectations. 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% [-]

Understand the purpose and key concepts of Deployment Management, highlighting its importance in managing the deployment of new or changed services into the live environment. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours of content   Mobile-optimised   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

En pivottabell er et kraftig verktøy i Microsoft Excel som gjør at du kan beregne, summere og analysere store mengder data på en rask og effektiv måte. En pivottabell kan brukes til å analysere numeriske data og til å besvare uventede spørsmål om dataen. Kort fortalt, en pivottabell hjelper deg med å ta informerte beslutninger basert på funnene i dataene dine. I dette kurset, ledet av Espen Faugstad, vil du lære alt du trenger å vite for å jobbe med pivottabeller i Microsoft Excel. Kurset vil dekke hva en pivottabell er, hvordan du klargjør data, organiserer data, formaterer data, presenterer data, og mye mer. For å ta dette kurset, bør du ha grunnleggende forståelse av Microsoft Excel. Kurset er strukturert i følgende kapitler: Kapittel 1: Introduksjon Kapittel 2: Grunnleggende Kapittel 3: Viderekommen Kapittel 4: Avslutning Etter å ha fullført kurset vil du være i stand til å bruke pivottabeller til å analysere data, trekke innsikter og ta informerte beslutninger basert på dataene i Excel.   Varighet: 1 time   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Vår tjeneste fungerer på samme måte som strømmetjenester for musikk eller TV-serier, der våre kunder betaler en fast månedspris for tilgang til alle kursene vi har tilgjengelig. Vi har opplevd betydelig vekst de siste årene, med over 30 000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling engasjerende, spennende og tilgjengelig for alle, og vi har støtte fra Innovasjon Norge og Forskningsrådet. [-]

Machine Learning and Data Science in R with Microsoft SQL Server - with Rafal Lukawiecki [-]

  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.    [-]

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 [-]

Dette kurset er skreddersydd for deltakere som allerede har fullført vårt grunnleggende Excel-kurs og nå ønsker å ta sine ferdigheter til et avansert nivå. Kursinstruktør Espen Faugstad vil veilede deg gjennom en rekke avanserte emner, inkludert opprettelse av pivottabeller, bruk av funksjoner og formler, og mye mer. Kurset dekker grundig bruken av en rekke funksjoner og formler, inkludert SUMMER, MIN, MAKS, AVKORT, AVRUND, ANTALL, ANTALLA, KJEDE.SAMMEN, TRIMME, VENSTRE, HØYRE, DELTEKST, FINN.RAD, HVIS, SUMMERHVIS, ANTALL.HVIS og GJENNOMSNITTHVIS. I tillegg vil kurset veilede deg gjennom henting av ekstern data, sortering og filtrering, fjerning av duplikater, og gruppering av data.   Innhold: Kapittel 1: Pivottabeller Kapittel 2: Formler og Funksjoner Kapittel 3: Formelrevisjon Kapittel 4: Ekstern Data Kapittel 5: Sortering og Filtrering Kapittel 6: Dataverktøy Kapittel 7: Gruppering av Data Kapittel 8: Arkbeskyttelse Kapittel 9: Avslutning   Varighet: 2 timer og 17 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Vår tjeneste fungerer på samme måte som strømmetjenester for musikk eller TV-serier, der våre kunder betaler en fast månedspris for tilgang til alle kursene vi har tilgjengelig. Vi har opplevd betydelig vekst de siste årene, med over 30 000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling engasjerende, spennende og tilgjengelig for alle, og vi har støtte fra Innovasjon Norge og Forskningsrådet. [-]

ENCOR: Implementing and Operating Cisco Enterprise Network Core Technologies [-]

Objectives This course teaches participants the following skills: Design and build data processing systems on Google Cloud Platform Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow Derive business insights from extremely large datasets using Google BigQuery Train, evaluate, and predict using machine learning models using Tensorflow and Cloud ML Leverage unstructured data using Spark and ML APIs on Cloud Dataproc Enable instant insights from streaming data   All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introduction to Data Engineering -Explore the role of a data engineer-Analyze data engineering challenges-Intro to BigQuery-Data Lakes and Data Warehouses-Demo: Federated Queries with BigQuery-Transactional Databases vs Data Warehouses-Website Demo: Finding PII in your dataset with DLP API-Partner effectively with other data teams-Manage data access and governance-Build production-ready pipelines-Review GCP customer case study-Lab: Analyzing Data with BigQuery Module 2: Building a Data Lake -Introduction to Data Lakes-Data Storage and ETL options on GCP-Building a Data Lake using Cloud Storage-Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions-Securing Cloud Storage-Storing All Sorts of Data Types-Video Demo: Running federated queries on Parquet and ORC files in BigQuery-Cloud SQL as a relational Data Lake-Lab: Loading Taxi Data into Cloud SQL Module 3: Building a Data Warehouse -The modern data warehouse-Intro to BigQuery-Demo: Query TB+ of data in seconds-Getting Started-Loading Data-Video Demo: Querying Cloud SQL from BigQuery-Lab: Loading Data into BigQuery-Exploring Schemas-Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA-Schema Design-Nested and Repeated Fields-Demo: Nested and repeated fields in BigQuery-Lab: Working with JSON and Array data in BigQuery-Optimizing with Partitioning and Clustering-Demo: Partitioned and Clustered Tables in BigQuery-Preview: Transforming Batch and Streaming Data Module 4: Introduction to Building Batch Data Pipelines -EL, ELT, ETL-Quality considerations-How to carry out operations in BigQuery-Demo: ELT to improve data quality in BigQuery-Shortcomings-ETL to solve data quality issues Module 5: Executing Spark on Cloud Dataproc -The Hadoop ecosystem-Running Hadoop on Cloud Dataproc-GCS instead of HDFS-Optimizing Dataproc-Lab: Running Apache Spark jobs on Cloud Dataproc Module 6: Serverless Data Processing with Cloud Dataflow -Cloud Dataflow-Why customers value Dataflow-Dataflow Pipelines-Lab: A Simple Dataflow Pipeline (Python/Java)-Lab: MapReduce in Dataflow (Python/Java)-Lab: Side Inputs (Python/Java)-Dataflow Templates-Dataflow SQL Module 7: Manage Data Pipelines with Cloud Data Fusion and Cloud Composer -Building Batch Data Pipelines visually with Cloud Data Fusion-Components-UI Overview-Building a Pipeline-Exploring Data using Wrangler-Lab: Building and executing a pipeline graph in Cloud Data Fusion-Orchestrating work between GCP services with Cloud Composer-Apache Airflow Environment-DAGs and Operators-Workflow Scheduling-Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, -Cloud Storage, and BigQuery-Monitoring and Logging-Lab: An Introduction to Cloud Composer Module 8: Introduction to Processing Streaming Data Processing Streaming Data Module 9: Serverless Messaging with Cloud Pub/Sub -Cloud Pub/Sub-Lab: Publish Streaming Data into Pub/Sub Module 10: Cloud Dataflow Streaming Features -Cloud Dataflow Streaming Features-Lab: Streaming Data Pipelines Module 11: High-Throughput BigQuery and Bigtable Streaming Features -BigQuery Streaming Features-Lab: Streaming Analytics and Dashboards-Cloud Bigtable-Lab: Streaming Data Pipelines into Bigtable Module 12: Advanced BigQuery Functionality and Performance -Analytic Window Functions-Using With Clauses-GIS Functions-Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz-Performance Considerations-Lab: Optimizing your BigQuery Queries for Performance-Optional Lab: Creating Date-Partitioned Tables in BigQuery Module 13: Introduction to Analytics and AI -What is AI?-From Ad-hoc Data Analysis to Data Driven Decisions-Options for ML models on GCP Module 14: Prebuilt ML model APIs for Unstructured Data -Unstructured Data is Hard-ML APIs for Enriching Data-Lab: Using the Natural Language API to Classify Unstructured Text Module 15: Big Data Analytics with Cloud AI Platform Notebooks -What’s a Notebook-BigQuery Magic and Ties to Pandas-Lab: BigQuery in Jupyter Labs on AI Platform Module 16: Production ML Pipelines with Kubeflow -Ways to do ML on GCP-Kubeflow-AI Hub-Lab: Running AI models on Kubeflow Module 17: Custom Model building with SQL in BigQuery ML -BigQuery ML for Quick Model Building-Demo: Train a model with BigQuery ML to predict NYC taxi fares-Supported Models-Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML-Lab Option 2: Movie Recommendations in BigQuery ML Module 18: Custom Model building with Cloud AutoML -Why Auto ML?-Auto ML Vision-Auto ML NLP-Auto ML Tables [-]

TARGET AUDIENCE Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C#, Python, or JavaScript and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure. COURSE OBJECTIVES After completing this course you should be able to: Describe considerations for creating AI-enabled applications Identify Azure services for AI application development Provision and consume cognitive services in Azure Manage cognitive services security Monitor cognitive services Use a cognitive services container Use the Text Analytics cognitive service to analyze text Use the Translator cognitive service to translate text Use the Speech cognitive service to recognize and synthesize speech Use the Speech cognitive service to translate speech Create a Language Understanding app Create a client application for Language Understanding Integrate Language Understanding and Speech Use QnA Maker to create a knowledge base Use a QnA knowledge base in an app or bot Use the Bot Framework SDK to create a bot Use the Bot Framework Composer to create a bot Use the Computer Vision service to analyze images Use Video Indexer to analyze videos Use the Custom Vision service to implement image classification Use the Custom Vision service to implement object detection Detect faces with the Computer Vision service Detect, analyze, and recognize faces with the Face service Use the Computer Vision service to read text in images and documents Use the Form Recognizer service to extract data from digital forms Create an intelligent search solution with Azure Cognitive Search Implement a custom skill in an Azure Cognitive Search enrichment pipeline Use Azure Cognitive Search to create a knowledge store   COURSE CONTENT Module 1: Introduction to AI on Azure Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly. Introduction to Artificial Intelligence Artificial Intelligence in Azure Module 2: Developing AI Apps with Cognitive Services Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy cognitive services. Getting Started with Cognitive Services Using Cognitive Services for Enterprise Applications Lab: Get Started with Cognitive Services Lab: Get Started with Cognitive Services Lab: Monitor Cognitive Services Lab: Use a Cognitive Services Container Module 3: Getting Started with Natural Language Processing  Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text. Analyzing Text Translating Text Lab: Analyze Text Lab: Translate Text Module 4: Building Speech-Enabled Applications Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications. Speech Recognition and Synthesis Speech Translation Lab: Recognize and Synthesize Speech Lab: Translate Speech Module 5: Creating Language Understanding Solutions To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you'll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input. Creating a Language Understanding App Publishing and Using a Language Understanding App Using Language Understanding with Speech Lab: Create a Language Understanding App Lab: Create a Language Understanding Client Application Use the Speech and Language Understanding Services Module 6: Building a QnA Solution One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution. Creating a QnA Knowledge Base Publishing and Using a QnA Knowledge Base Lab: Create a QnA Solution Module 7: Conversational AI and the Azure Bot Service Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences. Bot Basics Implementing a Conversational Bot Lab: Create a Bot with the Bot Framework SDK Lab: Create a Bot with a Bot Freamwork Composer Module 8: Getting Started with Computer Vision Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of computer vision by learning how to use cognitive services to analyze images and video. Analyzing Images Analyzing Videos Lab: Analyse Images with Computer Vision Lab: Analyze Images with Video Indexer Module 9: Developing Custom Vision Solutions While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you'll explore the Custom Vision service, and how to use it to create custom image classification and object detection models. Image Classification Object Detection Lab: Classify Images with Custom Vision Lab: Detect Objects in Images with Custom Vision Module 10: Detecting, Analyzing, and Recognizing Faces Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user of cognitive services to identify human faces. Detecting Faces with the Computer Vision Service Using the Face Service Lab:Destect, Analyze and Recognize Faces Module 11: Reading Text in Images and Documents Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms. Reading text with the Computer Vision Service Extracting Information from Forms with the Form Recognizer service Lab: Read Text in IMages Lab: Extract Data from Forms Module 12: Creating a Knowledge Mining Solution Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights. Implementing an Intelligent Search Solution Developing Custom Skills for an Enrichment Pipeline Creating a Knowledge Store Lab: Create and Azure Cognitive Search Solution Create a Custom Skill for Azure Cognitive Search Create a Knowledge Store with Azure Cognitive Search   TEST CERTIFICATION Recommended as preparation for the following exams: AI-102 - Designing and Implementing a Microsoft Azure AI Solution - Part of the requirements for the Microsoft Certified Azure AI Engineer Associate Certification.   HVORFOR VELGE SG PARTNER AS:  Flest kurs med Startgaranti Rimeligste kurs Beste service og personlig oppfølgning Tilgang til opptak etter endt kurs Partner med flere av verdens beste kursleverandører [-]

COURSE OVERVIEW This course is comprised of the following Microsoft Official Curriculum modules: MS-500T01 Managing Microsoft 365 Identity and Access, MS-500T02 Implementing Microsoft 365 Threat Protection, MS-500T03 Implementing Microsoft 365 Information Protection and MS-500T04 Administering Microsoft 365 Built-in Compliance.   MS-500T01 Managing Microsoft 365 Identity and Access Help protect against credential compromise with identity and access management. In this course you will learn how to secure user access to your organization’s resources. Specifically, this course covers user password protection, multi-factor authentication, how to enable Azure Identity Protection, how to configure Active Directory federation services, how to setup and use Azure AD Connect, and introduces you to Conditional Access. You will also learn about solutions for managing external access to your Microsoft 365 system.   MS500T02 Implementing Microsoft 365 Threat Protection Threat protection helps stop damaging attacks with integrated and automated security. In this course you will learn about threat protection technologies that help protect your Microsoft 365 environment. Specifically, you will learn about threat vectors and Microsoft’s security solutions for them. You will learn about Secure Score, Exchange Online protection, Azure Advanced Threat Protection, Windows Defender Advanced Threat Protection, and how to use Microsoft 365 Threat Intelligence. It also discusses securing mobile devices and applications. The goal of this course is to help you configure your Microsoft 365 deployment to achieve your desired security posture.   MS500T03 Implementing Microsoft 365 Information Protection Information protection is the concept of locating and classifying data anywhere it lives. In this course you will learn about information protection technologies that help secure your Microsoft 365 environment. Specifically, this course discusses information rights managed content, message encryption, as well as labels, policies and rules that support data loss prevention and information protection. Lastly, the course explains the deployment of Microsoft Cloud App Security.   MS500T04 Administering Microsoft 365 Built-in Compliance Internal policies and external requirements for data retention and investigation may be necessary for your organization. In this course you will learn about archiving and retention in Microsoft 365 as well as data governance and how to conduct content searches and investigations. Specifically, this course covers data retention policies and tags, in-place records management for SharePoint, email retention, and how to conduct content searches that support eDiscovery investigations. The course also helps your organization prepare for Global Data Protection Regulation (GDPR).   Virtual Learning   This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins. TARGET AUDIENCE This course is for the Microsoft 365 security administrator role. This role collaborates with the Microsoft 365 Enterprise Administrator, business stakeholders and other workload administrators to plan and implement security strategies and ensures that the solutions comply with the policies and regulations of the organization. COURSE CONTENT Module 1: User and Group Security This module explains how to manage user accounts and groups in Microsoft 365. It introduces you to Privileged Identity Management in Azure AD as well as Identity Protection. The module sets the foundation for the remainder of the course.   Module 2: Identity Synchronization This module explains concepts related to synchronizing identities. Specifically, it focuses on Azure AD Connect and managing directory synchronization to ensure the right people are connecting to your Microsoft 365 system.   Module 3: Federated Identities This module is all about Active Directory Federation Services (AD FS). Specifically, you will learn how to plan and manage AD FS to achieve the level of access you want to provide users from other directories.   Module 4: Access Management This module describes Conditional Access for Microsoft 365 and how it can be used to control access to resources in your organization. The module also explains Role Based Access Control (RBAC) and solutions for external access.   Module 5: Security in Microsoft 365 This module starts by explaining the various cyber-attack threats that exist. It then introduces you to the Microsoft solutions to thwart those threats. The module finishes with an explanation of Microsoft Secure Score and how it can be used to evaluate and report your organizations security posture.   Module 6: Advanced Threat Protection This module explains the various threat protection technologies and services available in Microsoft 365. Specifically, the module covers message protection through Exchange Online Protection, Azure Advanced Threat Protection and Windows Defender Advanced Threat Protection.   Module 7: Threat Intelligence This module explains Microsoft Threat Intelligence which provides you with the tools to evaluate and address cyber threats. You will learn how to use the Security Dashboard in the Microsoft 365 Security and Compliance Center. It also explains and configures Microsoft Advanced Threat Analytics.   Module 8: Mobility This module is all about securing mobile devices and applications. You will learn about Mobile Device Management and how it works with Intune. You will also learn about how Intune and Azure AD can be used to secure mobile applications.   Module 9: Information Protection This module explains information rights management in Exchange and SharePoint. It also describes encryption technologies used to secure messages. The module introduces how to implement Azure Information Protection and Windows Information Protection.   Module 10: Data Loss Prevention This module is all about data loss prevention in Microsoft 365. You will learn about how to create policies, edit rules, and customize user notifications.   Module 11: Cloud Application Security This module is all about cloud app security for Microsoft 365. The module will explain cloud discovery, app connectors, policies, and alerts.     [-]

In this course students will gain the knowledge and skills needed to implement security controls, maintain the security posture, and identify and remediate vulnerabilities by using a variety of security tools. The course covers scripting and automation, virtualization, and cloud N-tier architecture. TARGET AUDIENCE Students should have at least one year of hands-on experience securing Azure workloads and experience with security controls for workloads on Azure. COURSE OBJECTIVES Describe specialized data classifications on Azure Identify Azure data protection mechanisms Implement Azure data encryption methods Secure Internet protocols and how to implement them on Azure Describe Azure security services and features COURSE CONTENT Module 1: Identity and Access LESSONS Configure Azure Active Directory for Azure workloads and subscriptions Configure Azure AD Privileged Identity Management Configure security for an Azure subscription Module 2: Platform Protection LESSONS Understand cloud security Build a network Secure network Implement host security Implement platform security Implement subscription security Module 3: Security Operations LESSONS Configure security services Configure security policies by using Azure Security Center Manage security alerts Respond to and remediate security issues Create security baselines Module 4: Data and applications LESSONS Configure security policies to manage data Configure security for data infrastructure Configure encryption for data at rest Understand application security Implement security for application lifecycle Secure applications Configure and manage Azure Key Vault [-]

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. [-]