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

Oracle Database: Administration Workshop [-]

Blended Virtual CourseThe course is a hybrid of virtual training and self-study which will be a mixture of teaching using Microsoft Teams for short bursts at the beginning of the day, then setting work for the rest of the day and then coming back at the end of the day for another on-line session for any questions before setting homework in the form of practice exams for the evening. You do not have to install Microsoft Teams, you will receive a link and can access the course using the web browser.  Remote proctored examTake your exam from any location. Read about iSQI remote proctored exam here Requirements for the exam: The exam will be using Google Chrome and there is a plug-in that needs to be installed  You will need a laptop/PC with a camera and a microphone  A current ID with a picture    KursinnholdDette 3 dagers kurset er rettet mot de som arbeider med teknisk testanalyse og som ønsker ytterligere kompetanse innenfor området. TTA kurset er basert på Foundation kursets pensum og gir grunnleggende ferdigheter innnenfor teknisk testanalyse til deltakerne. Bouvet sine kursdeltakeres testresultater vs ISTQB gjennomsnitt   Course content The course provides essential skills for every Technical Test Analyst -recognising typical risks related to technical aspects of the system being developed- select and apply appropriate structural design techniques for the required level of coverage- to effectively participate in a variety of documentation reviews- to understand the technical issues and concepts in applying test automation Other skills that will be attained include:-the ability to perform static and dynamic analysis and identify the various defects that can be found using these techniques. Quality characteristics are as important and, in some instances, more important than functionality, participants will understand the types of quality characteristics that the technical tester should identify and test. Exam The ISTQB Advanced TTA exam is a 2-hour multiple choice exam with the pass mark being 65%. There is an extra 30 minutes allowed for candidates whose first language is not English. You must hold the ISTQB Foundation certificate in software testing in order to sit this exam. The exam is a remote proctored exam. [-]

Kursinnhold FINN.RAD() FINN.KOLONNE() XOPPSLAG() – den nye oppslagsfunksjonen. Super funksjonalitet INDEKS() / SAMMENLIGNE() [-]

SISE: Implementing and Configuring Cisco Identity Services Engine [-]

Dette kurset tilbys som bedriftsinternt kurs   Fra mars 2020 til oktober 2020 økte antall daglige teams-brukere på verdensbasis fra 44 millioner til 115 millioner. Dette er en enorm økning og for mange innebar det å bli kastet inn i noe nytt uten opplæring. Det som egentlig skulle gjøre arbeidsdagen lettere, lagde flere utfordringer.  Appen er brukervennlig og fungerer sømløst med de andre verktøyene i Microsoft 365, men appen vokser ettersom behovene endrer seg, og med 115 millioner brukere er behovene også mange. Microsoft Teams er derfor et stort verktøy for god og effektiv samhandling, men verktøyene kan være så gode de bare vil – dersom de som bruker det ikke er kjent med funksjonalitetene som gjør Microsoft sømløst. I løpet av kurset vil deltagere få en god oversikt på hva Teams er, hva det kan brukes for, og hvordan best mulig bruke det. Kurset gir også tips og triks for best practice, samt hvordan man kan holde seg oppdatert på ny funksjonalitet som kommer.    Metode: Digitalkurs: Kursholder holder informative økter med gjennomgang og demonstrasjoner av de viktigste verktøyene, hvordan de virker sammen, og hvordan du og dine kollegaer bruker de effektivt sammen. Kursdeltakerne vil ha mulighet til å stille spørsmål, enten muntlig eller skriftlig, avhengig av gruppestørrelsen.    Kurs på Bouvethuset på Majorstuen: Kursholdere vil bruke en kombinasjon av undervisning, demonstrasjoner og øvelser så deltagerne kan raskt komme i gang og samtidig bygge en bevisst og robust tilnærming til verktøyet. Deltagkerne får da mulighet til å teste ut funksjonalitet underveis i Bouvet sitt kursmiljø.    Målgruppe Alle som ønsker en grundig introduksjon og opplæring i Teams applikasjonen. Det passer både for deg som aldri har brukt Teams før, og for deg som ønsker å utvikle deg til superbruker. Spesielt egnet for deg som skal være med å spesifisere, tilrettelegge eller være ansvarlig for innføring av samhandlingsløsninger.   Kursinnhold •    Teams som del av Office 365 plattformen•    Oversikt over begreper, lisensmodeller og relatert•    Pålogging, navigasjon og grensesnitt i Teams•    Hvordan strukturere velfungerende Teams: kanaler, faner, og mer•    Fillagring og fildeling•    Samtaler, chat og virtuelle møter•    Samtidig redigering•    Beste praksiser, tips og triks•    Innstillinger og sikkerhet•    Administrasjon for Teams eiere•    Kontinuerlig læring i bruk av verktøyet•    Samhandlingsstrategier   [-]

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 [-]

AZ-900: Microsoft Azure Fundamentals [-]

Instruktørbasert opplæring:   PowerPoint nivå 4 - Utvikling av maler Lysbildemal Generelt om maloppsettet Flere lysbildemaler i samme presentasjon Definere temafarger Bytte lysbildemal i en presentasjon Gjøre maler tilgjengelig for "alle" Lysbildeoppsett Tilpasse eksisterende oppsett Lage egendefinerte lysbildeoppsett Kontrollere rekkefølgen på plassholdere   3 gode grunner til å delta 1. Få forståelse av hvordan malen fungerer 2. Lær hvordan temafarger styrer utseende 3. Se hvordan du kan tilpasse lysbildeoppsett, og hvordan lage egne [-]

AutoCAD 3D introduksjonskurs: Deltagerne skal kunne skille mellom ulike modelltyper, og kjenne til grunnprinsipper for 3D-modellering og bruk av koordinatsystem, samt beherske bruk av betraktningsvinkler og skjermnavigering. Koordinatsystemer Angivelse av punkter i rommet Solid modellering Surface modellering Mesh modellering Sette opp Layout i paperspace, projeksjoner og snitt Lagstruktur og lagdefinisjon, farger, linjetyper, målsetting Lyssetting, naturlig sollys og lokale lyskilder Knytte materialer til objekt eller til lag Renderfunksjoner Animasjon og video [-]

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 [-]

Advanced Architecting on AWS [-]

MB-220: Dynamics 365 Customer Insights - Journeys [-]

COURSE OVERVIEW You’ll learn how to implement and secure a wireless network infrastructure and use Cisco Identity Service Engine (ISE), Cisco Prime Infrastructure (PI), and Cisco Connect Mobile Experience to monitor and troubleshoot network issues.   The course provides hands-on labs to reinforce concepts including deploying Cisco Prime Infrastructure Release 3.5, Cisco Catalyst 9800 Wireless Controller Release IOS XE Gibraltar 16.10, Cisco Digital Network Architecture (DNA) Center Release 1.2.8, Cisco CMX Release 10.5, Cisco MSE Release 8.0 features and Cisco Identity Services Engine (ISE) Release 2.4.   This course also helps you prepare to take the Implementing Cisco Enterprise Wireless Networks (300-430 ENWLSI) exam, which is part of the new CCNP Enterprise certification. Passing the exam will also provide you with the Cisco Certified Specialist - Enterprise Wireless Implementation certification.   TARGET AUDIENCE Individuals needing to understand how to implement, secure and troubleshoot a Cisco Enterprise Wireless Network.   COURSE OBJECTIVES After completing this course you should be able to: Implement network settings to provide a secure wireless network infrastructure Troubleshoot security issues as it relates to the wireless network infrastructure Implement a secure wireless client and troubleshoot wireless client connectivity issues Implement and troubleshoot QoS in wireless networks Implement and troubleshoot advanced capabilities in wireless network services   COURSE CONTENT Securing and Troubleshooting the Wireless Network Infrastructure Implement Secure Access to the WLCs and Access Points Configure the Network for Access Point 802.1X Authentication Use Cisco DNA Center for Controller and AP Auto Install Implement Cisco Prime Infrastructure Define Network Troubleshooting Techniques Troubleshoot Access Point Join Issues Monitor the Wireless Network Implementing and Troubleshooting Secure Client Connectivity Configure the Cisco WLC for Wireless Client 802.1x Authentication Configure the Wireless Client for 802.1X Authentication Configure a Wireless LAN for FlexConnect Implement Guest Services in the Wireless Network Configure the Cisco WLC for Centralized Web Authentication Configure Central Web Authentication on Cisco ISE Implement BYOD Implement Location-Aware Guest Services Troubleshoot Client Connectivity Describe Issues that Affect Client Performance Monitor Wireless Clients Implementing and Troubleshooting QoS in Wireless Networks Implement QoS in the Wireless Network Configure the Cisco WLC to Support Voice Traffic Optimize Wireless Utilization on the Cisco WLC Implement Cisco AVC in the Wireless Network Implement Multicast Services Implement mDNS Service Implement Cisco Media Stream Troubleshoot QoS Issues in the Wireless Network Troublehoot mDNS Issues Troubleshoot Media Stream Issues Implementing and Troubleshooting Advanced Wireless Network Services Implement Base Location Services on Cisco Prime Infrastructure Implement Hyperlocation in the Wireless Network Implement Detect and Locate Services on Cisco CMX Implement Analytics on Cisco CMX Implement Presence Services on Cisco CMX Monitor and Locate Rogue Devices with Cisco Prime Infrastructure and Cisco CMX Monitor and Detect Wireless Clients with Cisco CMX and Cisco DNA Center Run Analytics on Wireless Clients Troubleshoot Location Accuracy with Cisco Hyperlocation Monitor and Manage RF Interferers on the Cisco WLC Monitor and Manager RF Interferers on Cisco Prime Infrastructure and Cisco CMX Labs Lab Familiarization (Base Learning Lab) Configure Secure Management Access for WLCs and APs Add Network Devices and External Resources to Cisco Prime Infrastructure Capture a Successful AP Authentication Implement AAA Services for Central Mode WLANs Implement AAA Services for FlexConnect Mode WLANs Configure Guest Services in the Wireless Network Configure BYOD in the Wireless Network Capture a Successful Client Authentications Configure QoS in the Wireless Network for Voice and Video Services Configure Cisco AVC in the Wireless Network Capture Successful QoS Traffic Marking in the Wireless Network Configure Detect and Locate Services on the Cisco CMX Identify Wireless Clients and Security Threats [-]

Developing on AWS [-]

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