Oversikt over relevante kurs innen IT-kurs i Trøgstad

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

Datagrunnlaget Gruppering Formatering Tallformater Visningsalternativer Feltinnstillinger Beregnede felt Bruk av flere pivottabeller i samme arbeidsbok Slicere som virker på flere pivottabeller eller pivotdiagrammer Tabellfunksjonalitet   Analyse av pivotdiagram Bruk av pivotdiagram i andre programmer   et er fordelaktig å ha to skjermer - en til å følge kurset og en til å gjøre det kursholder demonstrerer. Kurset gjennomføres i sanntid med nettundervisning via Teams. Det blir mulighet for å stille spørsmål, ha diskusjoner, demonstrasjoner og øvelser. Du vil motta en invitasjon til Teams fra kursholder.   [-]

Kursinnhold Enkle formler Cellereferanser Gi navn til celler og områder Feilkontroll og formelrevisjon Hente data fra andre ark og arbeidsbøker Egendefinerte tallformater Betinget formatering Utklippstavle og avansert innliming   Det er fordelaktig å ha to skjermer - en til å følge kurset og en til å gjøre det kursholder demonstrerer.   Kurset gjennomføres i sanntid med nettundervisning via Teams. Det blir mulighet for å stille spørsmål, ha diskusjoner, demonstrasjoner og øvelser. Du vil motta en invitasjon til Teams fra kursholder. [-]

Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform. Learning Objectives This course teaches participants the following skills: Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform Employ BigQuery and Cloud Datalab to carry out interactive data analysis Train and use a neural network using TensorFlow Employ ML APIs Choose between different data processing products on the Google Cloud Platform Course Outline Module 1: Introducing Google Cloud Platform -Google Platform Fundamentals Overview-Google Cloud Platform Big Data Products Module 2: Compute and Storage Fundamentals -CPUs on demand (Compute Engine)-A global filesystem (Cloud Storage)-CloudShell-Lab: Set up an Ingest-Transform-Publish data processing pipeline Module 3: Data Analytics on the Cloud -Stepping-stones to the cloud-CloudSQL: your SQL database on the cloud-Lab: Importing data into CloudSQL and running queries-Spark on Dataproc-Lab: Machine Learning Recommendations with Spark on Dataproc Module 4: Scaling Data Analysis -Fast random access-Datalab-BigQuery-Lab: Build machine learning dataset Module 5: Machine Learning -Machine Learning with TensorFlow-Lab: Carry out ML with TensorFlow-Pre-built models for common needs-Lab: Employ ML APIs Module 6: Data Processing Architectures -Message-oriented architectures with Pub/Sub-Creating pipelines with Dataflow-Reference architecture for real-time and batch data processing Module 7: Summary -Why GCP?-Where to go from here-Additional Resources [-]

Implementing REST Services using Web API [-]

AZ-700: Designing and Implementing Microsoft Azure Networking Solutions [-]

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

MD-101: Managing Modern Desktops [-]

Excelkurs Basis - elæringskurs [-]

. This course includes identity content for Azure AD, enterprise application registration, conditional access, identity governance, and other identity tools.   TARGET AUDIENCE This course is for the Identity and Access Administrators who are planning to take the associated certification exam, or who are performing identity and access administration tasks in their day-to-day job. This course would also be helpful to an administrator or engineer that wants to specialize in providing identity solutions and access management systems for Azure-based solutions; playing an integral role in protecting an organization. COURSE OBJECTIVES Implement an identity management solution Implement an authentication and access management solutions Implement access management for apps Plan and implement an identity governancy strategy COURSE CONTENT Module 1: Implement an identity management solution Learn to create and manage your initial Azure Active Directory (Azure AD) implementation and configure the users, groups, and external identities you will use to run your solution. Lessons M1 Implement Initial configuration of Azure AD Create, configure, and manage identities Implement and manage external identities Implement and manage hybrid identity Lab 1a: Manage user roles Lab 1b: Setting tenant-wide properties Lab 1c: Assign licenses to users Lab 1d: Restore or remove deleted users Lab 1e: Add groups in Azure AD Lab 1f: Change group license assignments Lab 1g: Change user license assignments Lab 1h: Configure external collaboration Lab 1i: Add guest users to the directory Lab 1j: Explore dynamic groups After completing module 1, students will be able to: Deploy an initail Azure AD with custom settings Manage both internal and external identities Implement a hybrid identity solution Module 2: Implement an authentication and access management solution Implement and administer your access management using Azure AD. Use MFA, conditional access, and identity protection to manager your identity solution. Lessons M2 Secure Azure AD user with MFA Manage user authentication Plan, implement, and administer conditional access Manage Azure AD identity protection Lab 2a: Enable Azure AD MFA Lab 2b: Configure and deploy self-service password reset (SSPR) Lab 2c: Work with security defaults Lab 2d: Implement conditional access policies, roles, and assignments Lab 2e: Configure authentication session controls Lab 2f: Manage Azure AD smart lockout values Lab 2g: Enable sign-in risk policy Lab 2h: Configure Azure AD MFA authentication registration policy After completing module 2, students will be able to: Configure and manage user authentication including MFA Control access to resources using conditional access Use Azure AD Identity Protection to protect your organization Module 3: Implement access management for Apps Explore how applications can and should be added to your identity and access solution with application registration in Azure AD. Lessons M3 Plan and design the integration of enterprise for SSO Implement and monitor the integration of enterprise apps for SSO Implement app registration Lab 3a: Implement access management for apps Lab 3b: Create a custom role to management app registration Lab 3c: Register an application Lab 3d: Grant tenant-wide admin consent to an application Lab 3e: Add app roles to applications and recieve tokens After completing module 3, students will be able to: Register a new application to your Azure AD Plan and implement SSO for enterprise application Monitor and maintain enterprise applications Module 4: Plan and implement an identity governancy strategy Design and implement identity governance for your identity solution using entitlement, access reviews, privileged access, and monitoring your Azure Active Directory (Azure AD). Lessons M4 Plan and implement entitlement management Plan, implement, and manage access reviews Plan and implement privileged access Monitor and maintain Azure AD Lab 4a: Creat and manage a resource catalog with Azure AD entitlement Lab 4b: Add terms of use acceptance report Lab 4c: Manage the lifecycle of external users with Azure AD identity governance Lab 4d: Create access reviews for groups and apps Lab 4e: Configure PIM for Azure AD roles Lab 4f: Assign Azure AD role in PIM Lab 4g: Assign Azure resource roles in PIM Lab 4h: Connect data from Azure AD to Azure Sentinel After completing module 4, students will be able to: Mange and maintain Azure AD from creation to solution Use access reviews to maintain your Azure AD Grant access to users with entitlement management [-]

Dette kurset er innrettet mot dem som jobber med økonomisk oppfølging i bedriften. Vi går inn på prosessene fra innhenting av data, bearbeidelse av dataene, sammendrag og analyse av dataene, og til sist rapportering av dataene til bedriftens beslutningstagere. Vi bruker en god del tid på Pivot og Power Pivot her, men vi går ikke fullt så langt som i spesialkurset om Pivottabeller. Kurset forutsetter at man er godt kjent i Excel, og vant til å jobbe med litt kompliserte problemstillinger i Excel. 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 Sentrale funksjoner, bl.a. HVIS, HVISFEIL, FINN.RAD, FINN.KOLONNE, ANTALL.HVIS, etc. Sammendrag av data med Pivottabell Power Pivot Formler Rapportering av data Statiske rapporter Rapporter med interaktivitet, forskjellige teknikker Visualisering av tallene Dashboard Aktuelle teknikker for å lage dashboards Avstemming av to eller flere lister mot hverandre, f.ex. bank Lister – verktøy i Excel som er aktuelle når vi jobber med lister Makroer/VBA – introduksjon til automatisering [-]

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 [-]

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  You will learn to deliver secure remote access to apps and desktops integrating Citrix Virtual Apps and Citrix Desktops with Citrix Gateway.  This course includes an exam. TARGET AUDIENCE Built for IT Professionals working with Citrix ADC and Gateway, with little or no previous Citrix networking experience. Potential students include administrators, engineers, and architects interested in learning how to deploy or manage Citrix ADC or Citrix Gateway environments. COURSE OBJECTIVES  Identify the functionality and capabilities of Citrix ADC and Citrix Gateway Explain basic Citrix ADC and Gateway network architecture Identify the steps and components to secure Citrix ADC Configure Authentication, Authorization, and Auditing Integrate Citrix Gateway with Citrix Virtual Apps, Citrix Virtual Desktops and other Citrix components COURSE CONTENT Module 1: Getting Started Introduction to Citrix ADC Feature and Platform Overview Deployment Options Architectural Overview Setup and Management Module 2: Basic Networking Networking Topology Citrix ADC Components Routing Access Control Lists Module 3: ADC Platforms Citrix ADC MPX Citrix ADC VPX Citrix ADC CPX Citrix ADC SDX Citrix ADC BLX Module 4: High Availability Citrix ADC High Availability High Availability Configuration Managing High Availability In Service Software Upgrade Troubleshooting High Availability Module 5: Load balancing Load Balancing Overview Load Balancing Methods and Monitors Load Balancing Traffic Types Load Balancing Protection Priority Load Balancing Load Balancing Troubleshooting Module 6: SSL Offloading SSL Overview SSL Configuration SSL Offload Troubleshooting SSL Offload SSL Vulnerabilities and Protections Module 7: Security Authentication, Authorization, and Auditing Configuring External Authentication Admin Partitions Module 8: Monitoring and Troubleshooting Citrix ADC Logging Monitoring with SNMP Reporting and Diagnostics AppFlow Functions Citrix Application Delivery Management Troubleshooting Module 9: Citrix Gateway Introduction to Citrix Gateway Advantages and Utilities of Citrix Gateway Citrix Gateway Configuration Common Deployments Module 10: AppExpert Expressions Introduction to AppExpert Policies Default Policies Explore Citrix ADC Gateway Policies Policy Bind Points Using AppExpert with Citrix Gateway Module 11: Authentication, Authorization, and Secure Web Gateway Authentication and Authorization Multi-Factor Authentication nFactor Visualizer SAML authentication Module 12: Managing Client Connections Introduction to Client Connections Session Policies and Profiles Pre and Post Authentication Policies Citrix Gateway Deployment Options Managing User Sessions Module 13: Integration for Citrix Virtual Apps and Desktops Virtual Apps and Desktop Integration Citrix Gateway Integration Citrix Gateway WebFront ICA Proxy Clientless Access and Workspace App Access Fallback SmartControl and SmartAccess for ICA Module 14: Configuring Citrix Gateway Working with Apps on Citrix Gateway RDP Proxy Portal Themes and EULA [-]

Objectives This course teaches participants the following skills: Identify the purpose and value of each of the Google Cloud Platform products and services Interact with Google Cloud Platform services Describe ways in which customers have used Google Cloud Platform Choose among and use application deployment environments on Google Cloud Platform: Google App Engine, Google Kubernetes Engine, and Google Compute Engine Choose among and use Google Cloud Platform storage options: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore Make basic use of BigQuery, Google’s managed data warehouse for analytics Make basic use of Cloud Deployment Manager, Google’s tool for creating and managing cloud resources through templates Make basic use of Google Stackdriver, Google’s monitoring, logging, and diagnostics system 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 Platform -Explain the advantages of Google Cloud Platform-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 Platform -Identify the purpose of projects on Google Cloud Platform-Understand the purpose of and use cases for Identity and Access Management-List the methods of interacting with Google Cloud Platform-Lab: Getting Started with Google Cloud Platform Module 3: Virtual Machines and Networks in the Cloud -Identify the purpose of and use cases for Google Compute Engine.-Understand the various Google Cloud Platform networking and operational tools and services.-Lab: Compute Engine Module 4: Storage in the Cloud -Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, Google Cloud Bigtable, and Google Cloud Datastore.-Learn how to choose between the various storage options on Google Cloud Platform.-Lab: Cloud Storage and Cloud SQL 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 Kubernetes Engine and Kubernetes.-Lab: Kubernetes Engine 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 the purpose of and use cases for Google Cloud Endpoints.-Lab: App Engine 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 the purpose of integrated monitoring, alerting, and debugging.-Lab: Deployment Manager and Stackdriver 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.-Lab: BigQuery [-]