Oversikt over relevante kurs innen IT-kurs i Tønsberg

Excel for Selgere - elæringskurs [-]

Excel Ekspert kurs for deg som ønsker en omfattende fordypning i Excel knyttet til formler og funksjoner, men som ikke har tid til å sette deg inn i dette på egenhånd. Vil du lære mer om håndtering av datagrunnlag og rapportering på grunnlag fra flere kilder, samt bygging av dynamiske modeller? Da er ”Excel Ekspert” kurset for deg! Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1   Funksjoner i Excel Utarbeidelse av dynamiske modeller ved bruk av navn og funksjoner. Funksjoner. Få oversikt over flere avanserte funksjoner samt se kraften av å bruke sammensatte funksjoner Navn. Bruk navn for å forenkle og tydeliggjøre formler og funksjoner. Lag dynamiske etiketter til diagrammer Matriseregning. Få en innføring i hvordan du kan jobbe med matrisefunksjonalitet i Excel.   Alternativknapper og kombinasjonsbokser Gjør modellene dine mer interaktive ved bruk av kontroller   Dag 2   Klargjøre data for beregninger ved bruk av PowerQuery Hva er PowerQuery? Lese inn data til PowerQuery fra ulike kilder Eksempel: tilføye og slå sammen Snu krysstabell Kobling til tekstfil med problemer Manglende struktur i kolonner. Lær hvordan du kan gjengi informasjon i regnearket slik at grunnlaget kan brukes til rapportering. Duplikater. Lær forskjellige måter å kvitte seg med duplikater på. Splitte informasjon. Lær forskjellige måter for å skille data i kolonner.   Beregninger ved bruk av Pivot Eksempel: prosentvis fordeling ”i år mot i fjor”. Pivotkonsolidering og datakonsolidering.   Makroer Innspilling av makro. Hvordan lage makroer for å automatisere rutinearbeid? Redigering av makroer. Lær hvordan makroer kan gjøres mer dynamiske, kombinert med navn og bruk av meldingsbokser og ”hvis” setninger. Demonstrere viktige VBA metoder 4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti     [-]

Ønsker du en kjapp og smertefri introduksjon i verdens mest populære bildebehandlingsprogram? Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:   Dag 1    Innføring Fargemodellene RGB og CMYK Beskjæring av bildet til trykk eller skjerm Utskriftsoppløsning og kameraoppløsning Forstå hvordan oppløsning fungerer Hva er de vanligste filformatene å jobbe i   Arbeidsmiljø Menyer og paletter. Hva inneholder disse, og hvordan får du fram det du ønsker? Tilpasse arbeidsmiljøet. Flytte på paletter og lagre egne oppsett tilpasset dine behov Navigering og zoom. Fokuser på det du jobber med, se helheten, og gjør dette raskt og effektivt Adobe Bridge. Introduksjon til programmet som organiserer og forhåndsviser filer og gjør det enklere for deg å jobbe Nytt dokument. Hvordan lage og tilpasse nye dokumenter med marger, spalter, sidevisning med mer?   Retusjering Bli kjent med retusjeringsverktøyene Se på hvilke muligheter du har i nyere utgave av Photoshop Fjerne uønskede elementer i bilder   Lag Bli kjent med lagpaletten Opprette, slette og organisere lag Transformering av lag Lagstiler og justeringslag   Markeringer Lær å bruke de forskjellige markeringsverktøyene Gjøre endringer på markerte områder Kombiner markeringsverktøy for å kun få tak i det du ønsker Opprett lag på bakgrunn av markeringer   Dag 2   Bildejusteringer Justere kontrast og tonalitet i et bilde Jobbe med å gjøre bilde lysere og mørkere Justere farger i et bilde Bytte ut én farge med en annen   Kombiner ulike verktøy for å utnytte mulighetene i Photoshop Jobbe med et bilde med ulike verktøy Markering og bildejustering Markering og fjerning av bakgrunnselementer Bruke smartere markedsverktøy   Lagring Lær om de ulike filformatene vi bør kjenne til Lagring til web og komprimering av bilder Lagring til trykk   Jobbe med flere bilder Klippe ut fra et bilde og lime inn i et annet Tekstverktøyet og tekstpalettene Tegneverktøy   4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

Excel – Du trodde du kunne det? [-]

Dette grunnleggende kurset om Microsoft Azure gir deg en solid forståelse av fundamentale konsepter i Azure-skymiljøet. Kursholderen, seniorutvikler John Inge Muldal Erlandsen, vil veilede deg gjennom nøkkelkomponentene og mulighetene som Azure tilbyr. Microsoft Azure er en ledende skyplattform og konkurrerer direkte med Amazon Web Services (AWS). Azure inneholder et bredt spekter av enheter, funksjoner og tjenester som du kan bruke for å oppfylle ulike behov innen skytjenester. Dette kurset er spesielt rettet mot forberedelse til AZ-900-eksamen, som fører til Microsoft-sertifiseringen "Microsoft Certified Fundamentals". Målet med kurset er å gi deg tilstrekkelig kunnskap og forberedelse til å bestå denne eksamenen med suksess. Kurset vil dekke følgende emner: Kapittel 1: Introduksjon Kapittel 2: Tjenester Kapittel 3: Verktøy Kapittel 4: Sikkerhet Kapittel 5: Styring Kapittel 6: Administrasjon Kapittel 7: Avslutning   Varighet: 4 timer og 32 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. [-]

This course is ideal for individuals or teams who wish to build a solid understanding of ArchiMate 3 and develop architecture artifacts using ArchiMate. What's new in ArchiMate 3.0? Like ArchiMate 2, ArchiMate 3 is a comprehensive modeling language that allows architects to create commonly understood and integrated visualizations of the essential enterprise architecture domains. Published as an Open Group Standard in June 2016, the ArchiMate 3 specification is a major update to ArchiMate 2.1. New features in version 3 include:• New concepts - Strategy and Motivation• New entities – Application, Technology and Implementation layers• Better ways to connect planning with implementation• Improvements in cross-layer relationships• New ‘Physical’ layer• Improvements in the viewpoints definition mechanism   Examination Certification in ArchiMate requires you to pass both a Foundation exam and a Certified exam.The Foundation exam is a closed book, multiple choice exam consisting of 40 questions. There is a time limit of 60 minutes and the pass-rate is 60%.After passing the Foundation exam you can then move onto the Practitioner exam, which is an open book, multiple choice exam consisting of eight questions. There is a time limit of 90 minutes and the pass-rate is 70%.A number of exercises are interspersed throughout the course, which are aimed at testing your understanding and practical application of the training you have just received. At the end of the course, a number of mock-exam case study scenarios are provided which have been designed to simulate the actual exam.After passing both exams you will become a certified ArchiMate 3 Practitioner! [-]

Power BI Desktop [-]

Python Data Science [-]

The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. After completing this course, students will be able to: Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics Course prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.Recommended prerequisites:M-DP900 - Microsoft Azure Data FundamentalsM-AZ900 - Microsoft Azure Fundamentals Agenda Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Module 16: Build reports using Power BI integration with Azure Synapase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. [-]

  An Azure IoT Developer is responsible for implementing and then maintaining the cloud and edge portions of an Azure IoT solution. In addition to configuring and maintaining devices by using Azure IoT services and other Microsoft tools, the IoT Developer also sets up the physical devices and is responsible for maintaining the devices throughout the life cycle. The IoT Developer implements designs for IoT solutions, including device topology, connectivity, debugging and security. For Edge device scenarios, the IoT Developer also deploys compute/containers and configures device networking, which could include various edge gateway implementations. The IoT Developer implements designs for solutions to manage data pipelines, including monitoring and data transformation as it relates to IoT. The IoT Developer works with data engineers and other stakeholders to ensure successful business integration. IoT Developers should have a good understanding of Azure services, including data storage options, data analysis, data processing, and the Azure IoT PaaS versus SaaS options. After completing this course, students will be able to: Create, configure, and manage an Azure IoT hub. Provision devices by using IoT Hub and DPS, including provisioning at scale. Establish secure 2-way communication between devices and IoT Hub. Implement message processing by using IoT Hub routing and Azure Stream Analytics. Configure the connection to Time Series Insights and support business integration requirements. Implement IoT Edge scenarios using marketplace modules and various edge gateway patterns. Implement IoT Edge scenarios that require developing and deploying custom modules and containers. Implement device management using device twins and direct methods. Implement solution monitoring, logging, and diagnostics testing. Recognize and address security concerns and implement Azure Security Center for IoT. Build an IoT Solution by using Azure IoT Central and recongize SaaS opportunities for IoT. Course prerequisites IoT Developers should have basic programming skills in at least one Azure-supported language, including C#, Node.js, C, Python, or Java. Software development experience is a prerequisite for this course, but no specific software language is required, and the experience does not need to be at a professional level. Data Processing Experience: General understanding of data storage and data processing is a recommended but not required.  Cloud Solution Awareness: Students should have a basic understanding of PaaS, SaaS, and IaaS implementations. Microsoft Azure Fundamentals (M-AZ-900T00/M-AZ900), or equivalent skills, is recommended.  This course helps to prepare for exam AZ-220.   Agenda Module 1: Introduction to IoT and Azure IoT Services -Business Opportunities for IoT-Introduction to IoT Solution Architecture-IoT Hardware and Cloud Services Module 2: Devices and Device Communication -IoT Hub and Devices-IoT Developer Tools-Device Configuration and Communication Module 3: Device Provisioning at Scale -Device Provisioning Service Terms and Concepts-Configure and Manage the Device Provisioning Service-Device Provisioning Tasks Module 4: Message Processing and Analytics -Messages and Message Processing-Data Storage Options-Azure Stream Analytics Module 5: Insights and Business Integration -Business Integration for IoT Solutions-Data Visualization with Time Series Insights-Data Visualization with Power BI Module 6: Azure IoT Edge Deployment Process -Introduction to Azure IoT Edge-Edge Deployment Process-Edge Gateway Devices Module 7: Azure IoT Edge Modules and Containers -Develop Custom Edge Modules-Offline and Local Storage Module 8: Device Management -Introduction to IoT Device Management-Manage IoT and IoT Edge Devices-Device Management at Scale Module 9: Solution Testing, Diagnostics, and Logging -Monitoring and Logging-Troubleshooting Module 10: Azure Security Center and IoT Security Considerations -Security Fundamentals for IoT Solutions-Introduction to Azure Security Center for IoT-Enhance Protection with Azure Security Center for IoT Agents Module 11: Build an IoT Solution with IoT Central -Introduction to IoT Central-Create and Manage Device Templates-Manage Devices in Azure IoT Central [-]

CCSP: Certified Cloud Security Professional [-]

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

NTI leverer opplæring for å forenkle og effektivisere din arbeidshverdag Årlig utdanner over 8.000 personer seg i ulike CAD- og BIM-løsninger hos NTI.Vi har mer enn 70 forskjellige kurs innen fagområdene CAD/BIM-, Industri, Prosess, Plant og Infrastruktur- og dokumenthåndtering, og i snitt har våre 100 konsulenter og instruktører mer enn 10 års erfaring med opplæring og konsulenttjenester. Hvordan få riktig oppsett av koordinater i prosjekt? Dette er et tema NTI merker stor pågang rundt til support, og henvendelsene kommer fra disipliner som byggteknikk, VVS og elektro i tillegg til arkitekt. Det er ofte arkitekten som setter opp koordinatene i Revit. Hvis utgangspunktet er feil, påvirkes dette i alle andre disipliner også. Spesielt der det er krav til at utvekslingsformatet er IFC. På dette online-kurset vil du lære: Forskjellen mellom de ulike koordinatsystemene Hva er et lokalt nullpunkt Sette opp reelle koordinater (Survey) «Best Practice» i oppsett av koordinater fra start Samhandling ved utveksling av filer og koordinater Behandle flere koordinatsystemer i samme prosjekt IFC export/import i forhold til delte koordinater Det kan gå noe tid mellom hver gang du setter opp koordinater, og det er lett å glemme prosessen. Etter gjennomført kurs, får du en «step by step» dokumentasjon, som kan benyttes som oppslagsverk senere.  Kurs på dine betingelser!Ditt firma har kanskje investert i ny CAD-programvare, oppgradert til ny versjon, oppdatert til ny programvare eller dere trenger rett og slett oppfriskning. Da er det på tide å investere i kompetanse for dine ansatte! Kontakt vår kurskoordinator Wenche, telefon 21 40 27 89 eller epost. [-]

Kurset passer for deg som har brukt Focus Arealplan en stund og ønsker å kunne utnytte programmet enda bedre. Focus Arealplan er i stadig utvikling og har nå enda flere muligheter når den brukes sammen med AutoCAD Civil 3D og Autodesk InfraWorks. På dette kurset lærer du mer avansert bruk av programmet og hvordan du tar i bruk det som er nytt i programmet. Kursinnhold 2018 innholdsoversikt Tips til oppstart av plan (hva bør man ta spesielt hensyn til) Arbeidsmetodikk ved store planer (Feilsøking med Quick select, Mapclean, Dynamisk geometrikontroll) Planer med flere vertikalnivåer, arbeidsmetodikk Presentasjonstegninger, også ifm. flere vertikalnivåer 3D-funksjoner, inkludert terrengsnitt av plan, også med flere vertikalnivåer Viewframes (tegningsrammer). Spesielt nyttig for lange planer, veiplaner og vridde planer. (AutoCAD Civil 3D) Modifisering av arkstørrelse Standard pennoppsett Konvertering av hele Novapoint-planer til Focus-Arealplan-objekter. Konvertering av enkelt-objekter eller enkelt-lag fra Autocad- eller Civil 3D-tegninger Illustrasjonsverktøy InfraWorks Tips for kontroll av geometri Tips for ekstern kontroll av planen i SOSI-kontroll   [-]

. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions.   TARGET AUDIENCE Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.   COURSE CONTENT Module 1: Creating Azure App Service Web Apps Students will learn how to build a web application on the Azure App Service platform. They will learn how the platform functions and how to create, configure, scale, secure, and deploy to the App Service platform. Azure App Service core concepts Creating an Azure App Service Web App Configuring and Monitoring App Service apps Scaling App Service apps Azure App Service staging environments Module 2: Implement Azure functions This module covers creating Functions apps, and how to integrate triggers and inputs/outputs in to the app. Azure Functions overview Developing Azure Functions Implement Durable Functions Module 3: Develop solutions that use blob storage Students will learn how Azure Blob storage works, how to manage data through the hot/cold/archive blob storage lifecycle, and how to use the Azure Blob storage client library to manage data and metadata. Azure Blob storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Module 4: Develop solutions that use Cosmos DB storage Students will learn how Cosmos DB is structured and how data consistency is managed. Students will also learn how to create Cosmos DB accounts and create databases, containers, and items by using a mix of the Azure Portal and the .NET SDK. Azure Cosmos DB overview Azure Cosmos DB data structure Working with Azure Cosmos DB resources and data Module 5: Implement IaaS solutions This module instructs students on how to use create VMs and container images to use in their solutions. It covers creating VMs, using ARM templates to automate resource deployment, create and manage Docker images, publishing an image to the Azure Container Registry, and running a container in Azure Container Instances. Provisioning VMs in Azure Create and deploy ARM templates Create container images for solutions Publish a container image to Azure Container Registry Create and run container images in Azure Container Instances Module 6: Implement user authentication and authorization Students will learn how to leverage the Microsoft Identity Platform v2.0 to manage authentication and access to resources. Students will also learn how to use the Microsoft Authentication Library and Microsoft Graph to authenticate a user and retrieve information stored in Azure, and how and when to use Shared Access Signatures. Microsoft Identity Platform v2.0 Authentication using the Microsoft Authentication Library Using Microsoft Graph Authorizing data operations in Azure Storage Module 7: Implement secure cloud solutions This module covers how to secure the information (keys, secrets, certificates) an application uses to access resources. It also covers securing application configuration information. Manage keys, secrets, and certificates by using the KeyVault API Implement Managed Identities for Azure resources Secure app configuration data by using Azure App Configuration Module 8: Implement API Management Students will learn how to publish APIs, create policies to manage information shared through the API, and to manage access to their APIs by using the Azure API Management service. API Management overview Defining policies for APIs Securing your APIs Module 9: Develop App Service Logic Apps This module teaches students how to use Azure Logic Apps to schedule, automate, and orchestrate tasks, business processes, workflows, and services across enterprises or organizations. Azure Logic Apps overview Creating custom connectors for Logic Apps Module 10: Develop event-based solutions Students will learn how to build applications with event-based architectures. Implement solutions that use Azure Event Grid Implement solutions that use Azure Event Hubs Implement solutions that use Azure Notification Hubs Module 11: Develop message-based solutions Students will learn how to build applications with message-based architectures. Implement solutions that use Azure Service Bus Implement solutions that use Azure Queue Storage queues Module 12: Monitor and optimize Azure solutions This module teaches students how to instrument their code for telemetry and how to analyze and troubleshoot their apps. Overview of monitoring in Azure Instrument an app for monitoring Analyzing and troubleshooting apps Implement code that handles transient faults Module 13: Integrate caching and content delivery within solutions Students will learn how to use different caching services to improve the performance of their apps. Develop for Azure Cache for Redis Develop for storage on CDNs [-]