1652 Database courses in Immingham delivered Online

Duration 4 Days 24 CPD hours This course is intended for 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 Sentinel, Microsoft Defender for Cloud, 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. Learn how to investigate, respond to, and hunt for threats using Microsoft Sentinel, Microsoft Defender for Cloud, and Microsoft 365 Defender. In this course you will learn how to mitigate cyberthreats using these technologies. Specifically, you will configure and use Microsoft 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. Prerequisites Basic understanding of Microsoft 365 Fundamental understanding of Microsoft security, compliance, and identity products Intermediate understanding of Windows 10 Familiarity with Azure services, specifically Azure SQL Database and Azure Storage Familiarity with Azure virtual machines and virtual networking Basic understanding of scripting concepts. 1 - Introduction to Microsoft 365 threat protection Explore Extended Detection & Response (XDR) response use cases Understand Microsoft Defender XDR in a Security Operations Center (SOC) Explore Microsoft Security Graph Investigate security incidents in Microsoft Defender XDR 2 - Mitigate incidents using Microsoft 365 Defender Use the Microsoft Defender portal Manage incidents Investigate incidents Manage and investigate alerts Manage automated investigations Use the action center Explore advanced hunting Investigate Microsoft Entra sign-in logs Understand Microsoft Secure Score Analyze threat analytics Analyze reports Configure the Microsoft Defender portal 3 - Protect your identities with Microsoft Entra ID Protection Microsoft Entra ID Protection overview Detect risks with Microsoft Entra ID Protection policies Investigate and remediate risks detected by Microsoft Entra ID Protection 4 - Remediate risks with Microsoft Defender for Office 365 Automate, investigate, and remediate Configure, protect, and detect Simulate attacks 5 - Safeguard your environment with Microsoft Defender for Identity Configure Microsoft Defender for Identity sensors Review compromised accounts or data Integrate with other Microsoft tools 6 - Secure your cloud apps and services with Microsoft Defender for Cloud Apps Understand the Defender for Cloud Apps Framework Explore your cloud apps with Cloud Discovery Protect your data and apps with Conditional Access App Control Walk through discovery and access control with Microsoft Defender for Cloud Apps Classify and protect sensitive information Detect Threats 7 - Respond to data loss prevention alerts using Microsoft 365 Describe data loss prevention alerts Investigate data loss prevention alerts in Microsoft Purview Investigate data loss prevention alerts in Microsoft Defender for Cloud Apps 8 - Manage insider risk in Microsoft Purview Insider risk management overview Create and manage insider risk policies Investigate insider risk alerts Take action on insider risk alerts through cases Manage insider risk management forensic evidence Create insider risk management notice templates 9 - Investigate threats by using audit features in Microsoft Defender XDR and Microsoft Purview Standard Explore Microsoft Purview Audit solutions Implement Microsoft Purview Audit (Standard) Start recording activity in the Unified Audit Log Search the Unified Audit Log (UAL) Export, configure, and view audit log records Use audit log searching to investigate common support issues 10 - Investigate threats using audit in Microsoft Defender XDR and Microsoft Purview (Premium) Explore Microsoft Purview Audit (Premium) Implement Microsoft Purview Audit (Premium) Manage audit log retention policies Investigate compromised email accounts using Purview Audit (Premium) 11 - Investigate threats with Content search in Microsoft Purview Explore Microsoft Purview eDiscovery solutions Create a content search View the search results and statistics Export the search results and search report Configure search permissions filtering Search for and delete email messages 12 - Protect against threats with Microsoft Defender for Endpoint Practice security administration Hunt threats within your network 13 - Deploy the Microsoft Defender for Endpoint environment Create your environment Understand operating systems compatibility and features Onboard devices Manage access Create and manage roles for role-based access control Configure device groups Configure environment advanced features 14 - Implement Windows security enhancements with Microsoft Defender for Endpoint Understand attack surface reduction Enable attack surface reduction rules 15 - Perform device investigations in Microsoft Defender for Endpoint Use the device inventory list Investigate the device Use behavioral blocking Detect devices with device discovery 16 - Perform actions on a device using Microsoft Defender for Endpoint Explain device actions Run Microsoft Defender antivirus scan on devices Collect investigation package from devices Initiate live response session 17 - Perform evidence and entities investigations using Microsoft Defender for Endpoint Investigate a file Investigate a user account Investigate an IP address Investigate a domain 18 - Configure and manage automation using Microsoft Defender for Endpoint Configure advanced features Manage automation upload and folder settings Configure automated investigation and remediation capabilities Block at risk devices 19 - Configure for alerts and detections in Microsoft Defender for Endpoint Configure advanced features Configure alert notifications Manage alert suppression Manage indicators 20 - Utilize Vulnerability Management in Microsoft Defender for Endpoint Understand vulnerability management Explore vulnerabilities on your devices Manage remediation 21 - Plan for cloud workload protections using Microsoft Defender for Cloud Explain Microsoft Defender for Cloud Describe Microsoft Defender for Cloud workload protections Enable Microsoft Defender for Cloud 22 - Connect Azure assets to Microsoft Defender for Cloud Explore and manage your resources with asset inventory Configure auto provisioning Manual log analytics agent provisioning 23 - Connect non-Azure resources to Microsoft Defender for Cloud Protect non-Azure resources Connect non-Azure machines Connect your AWS accounts Connect your GCP accounts 24 - Manage your cloud security posture management? Explore Secure Score Explore Recommendations Measure and enforce regulatory compliance Understand Workbooks 25 - Explain cloud workload protections in Microsoft Defender for Cloud Understand Microsoft Defender for servers Understand Microsoft Defender for App Service Understand Microsoft Defender for Storage Understand Microsoft Defender for SQL Understand Microsoft Defender for open-source databases Understand Microsoft Defender for Key Vault Understand Microsoft Defender for Resource Manager Understand Microsoft Defender for DNS Understand Microsoft Defender for Containers Understand Microsoft Defender additional protections 26 - Remediate security alerts using Microsoft Defender for Cloud Understand security alerts Remediate alerts and automate responses Suppress alerts from Defender for Cloud Generate threat intelligence reports Respond to alerts from Azure resources 27 - Construct KQL statements for Microsoft Sentinel Understand the Kusto Query Language statement structure Use the search operator Use the where operator Use the let statement Use the extend operator Use the order by operator Use the project operators 28 - Analyze query results using KQL Use the summarize operator Use the summarize operator to filter results Use the summarize operator to prepare data Use the render operator to create visualizations 29 - Build multi-table statements using KQL Use the union operator Use the join operator 30 - Work with data in Microsoft Sentinel using Kusto Query Language Extract data from unstructured string fields Extract data from structured string data Integrate external data Create parsers with functions 31 - Introduction to Microsoft Sentinel What is Microsoft Sentinel? How Microsoft Sentinel works When to use Microsoft Sentinel 32 - Create and manage Microsoft Sentinel workspaces Plan for the Microsoft Sentinel workspace Create a Microsoft Sentinel workspace Manage workspaces across tenants using Azure Lighthouse Understand Microsoft Sentinel permissions and roles Manage Microsoft Sentinel settings Configure logs 33 - Query logs in Microsoft Sentinel Query logs in the logs page Understand Microsoft Sentinel tables Understand common tables Understand Microsoft Defender XDR tables 34 - Use watchlists in Microsoft Sentinel Plan for watchlists Create a watchlist Manage watchlists 35 - Utilize threat intelligence in Microsoft Sentinel Define threat intelligence Manage your threat indicators View your threat indicators with KQL 36 - Connect data to Microsoft Sentinel using data connectors Ingest log data with data connectors Understand data connector providers View connected hosts 37 - Connect Microsoft services to Microsoft Sentinel Plan for Microsoft services connectors Connect the Microsoft Office 365 connector Connect the Microsoft Entra connector Connect the Microsoft Entra ID Protection connector Connect the Azure Activity connector 38 - Connect Microsoft Defender XDR to Microsoft Sentinel Plan for Microsoft Defender XDR connectors Connect the Microsoft Defender XDR connector Connect Microsoft Defender for Cloud connector Connect Microsoft Defender for IoT Connect Microsoft Defender legacy connectors 39 - Connect Windows hosts to Microsoft Sentinel Plan for Windows hosts security events connector Connect using the Windows Security Events via AMA Connector Connect using the Security Events via Legacy Agent Connector Collect Sysmon event logs 40 - Connect Common Event Format logs to Microsoft Sentinel Plan for Common Event Format connector Connect your external solution using the Common Event Format connector 41 - Connect syslog data sources to Microsoft Sentinel Plan for syslog data collection Collect data from Linux-based sources using syslog Configure the Data Collection Rule for Syslog Data Sources Parse syslog data with KQL 42 - Connect threat indicators to Microsoft Sentinel Plan for threat intelligence connectors Connect the threat intelligence TAXII connector Connect the threat intelligence platforms connector View your threat indicators with KQL 43 - Threat detection with Microsoft Sentinel analytics What is Microsoft Sentinel Analytics? Types of analytics rules Create an analytics rule from templates Create an analytics rule from wizard Manage analytics rules 44 - Automation in Microsoft Sentinel Understand automation options Create automation rules 45 - Threat response with Microsoft Sentinel playbooks What are Microsoft Sentinel playbooks? Trigger a playbook in real-time Run playbooks on demand 46 - Security incident management in Microsoft Sentinel Understand incidents Incident evidence and entities Incident management 47 - Identify threats with Behavioral Analytics Understand behavioral analytics Explore entities Display entity behavior information Use Anomaly detection analytical rule templates 48 - Data normalization in Microsoft Sentinel Understand data normalization Use ASIM Parsers Understand parameterized KQL functions Create an ASIM Parser Configure Azure Monitor Data Collection Rules 49 - Query, visualize, and monitor data in Microsoft Sentinel Monitor and visualize data Query data using Kusto Query Language Use default Microsoft Sentinel Workbooks Create a new Microsoft Sentinel Workbook 50 - Manage content in Microsoft Sentinel Use solutions from the content hub Use repositories for deployment 51 - Explain threat hunting concepts in Microsoft Sentinel Understand cybersecurity threat hunts Develop a hypothesis Explore MITRE ATT&CK 52 - Threat hunting with Microsoft Sentinel Explore creation and management of threat-hunting queries Save key findings with bookmarks Observe threats over time with livestream 53 - Use Search jobs in Microsoft Sentinel Hunt with a Search Job Restore historical data 54 - Hunt for threats using notebooks in Microsoft Sentinel Access Azure Sentinel data with external tools Hunt with notebooks Create a notebook Explore notebook code

Experience the future of geographical analysis with our Machine Learning for Predictive Maps in Python and Leaflet course. Master the unique blend of programming, machine learning, and geographic information systems, all while honing your ability to predict and visualise spatial data in a powerful and effective way. This course offers you an unparalleled understanding of modern map creation, combined with the magic of prediction using machine learning models. Starting from the ground up, you'll be introduced to all the necessary setups and installations. After that, you will be diving into the depth of Django server-side code and front-end application code writing. The heart of the course lies in learning how to automate the machine learning pipeline, leading you to easily create predictive models.  Improve your maps with Leaflet programming, making your predictions accurate and also visually striking. By the end of this course, you will be armed with experience furnished by our comprehensive project source code and assignments, empowering you to drive data-driven decisions and insightful spatial analysis. Join us and map your way to success! Sign up today. Learning Outcomes:Upon completion of the Machine Learning course, you will be able to: Understand how to set up and install relevant software and libraries.Master Django server-side and application front-end code writing.Gain proficiency in the concepts and implementation of Machine Learning.Learn to automate Machine Learning pipelines for efficient workflows.Acquire skills in Leaflet programming for enhanced map visuals.Handle project source code effectively for real-world projects.Apply knowledge practically via assignments and gain experience. Who is this course for?This Machine Learning course is ideal for: Aspiring Data Scientists keen on harnessing geographical data.GIS professionals aiming to integrate Machine Learning into their skill set.Software Developers interested in creating geographically-focused applications.Analysts keen on enhancing their data visualisation skills with mapping. CertificationAfter studying the course materials of the Machine Learning for Predictive Maps in Python and Leaflet course, there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test, you have a range of certification options to choose from. You can claim a CPD Accredited PDF Certificate for £4.99, a CPD Accredited Hardcopy Certificate at £8.00, or you may choose to receive a PDF Transcript for £4.99 or a Hardcopy Transcript for £9.99. Select according to your needs, and we assure timely delivery of your chosen certificate. RequirementsThis professionally designed Machine Learning for Predictive Maps in Python and Leaflet course does not require you to have any prior qualifications or experience. It is open to everyone. You will be able to access the course from anywhere at any time. Just enrol and start learning! Career Path:Our Machine Learning course will help you to pursue a range of career paths, such as: Junior Data Analyst: £25,000 - £35,000 annually.Data Scientist: £40,000 - £60,000 annually.GIS Analyst: £30,000 - £45,000 annually.Geospatial Software Developer: £35,000 - £55,000 annually.Machine Learning Engineer: £50,000 - £80,000 annually.Lead Data Scientist (GIS speciality): £70,000 - £100,000+ annually. Course Curriculum Section 01: Introduction Introduction 00:10:00 Section 02: Setup and Installations Python Installation 00:04:00 Creating a Python Virtual Environment 00:07:00 Installing Django 00:09:00 Installing Visual Studio Code IDE 00:06:00 Installing PostgreSQL Database Server Part 1 00:03:00 Installing PostgreSQL Database Server Part 2 00:09:00 Section 03: Writing the Django Server-Side Code Adding the settings.py Code 00:07:00 Creating a Django Model 00:10:00 Adding the admin.py Code 00:21:00 Section 04: Writing the Application Front-end Code Creating Template Files 00:10:00 Creating Django Views 00:10:00 Creating URL Patterns for the REST API 00:09:00 Adding the index.html code 00:04:00 Adding the layout.html code 00:19:00 Creating our First Map 00:10:00 Adding Markers 00:16:00 Section 05: Machine Learning Installing Jupyter Notebook 00:07:00 Data Pre-processing 00:31:00 Model Selection 00:20:00 Model Evaluation and Building a Prediction Dataset 00:11:00 Section 06: Automating the Machine Learning Pipeline Creating a Django Model 00:04:00 Embedding the Machine Learning Pipeline in the Application 00:42:00 Creating a URL Endpoint for our Prediction Dataset 00:06:00 Section 07: Leaflet Programming Creating Multiple Basemaps 00:09:00 Creating the Marker Layer Group 00:10:00 Creating the Point Layer Group 00:12:00 Creating the Predicted Point Layer Group 00:07:00 Creating the Predicted High Risk Point Layer Group 00:12:00 Creating the Legend 00:09:00 Creating the Prediction Score Legend 00:15:00 Section 08: Project Source Code Resource 00:00:00 Assignment Assignment - Machine Learning for Predictive Maps in Python and Leaflet 00:00:00

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This course covers the important topics needed to pass the AWS Certified Data Analytics-Specialty exam (AWS DAS-C01). You will learn about Kinesis, EMR, DynamoDB, and Redshift, and get ready for the exam by working through quizzes, exercises, and practice exams, along with exploring essential tips and techniques.

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Course Content Section 01: Introduction Introduction 00:08:00 Section 02: Building a Spatial Database using PostgreSQL and PostGIS Installing PostgreSQL and PostGIS Part1 00:10:00 Installing PostgreSQL and PostGIS Part2 00:10:00 Section 03: Building a GeoDjango Application Installing Python Django in a Virtual Environment 00:10:00 Installing and Configuring Atom IDE Part1 00:10:00 Installing and Configuring Atom IDE Part2 00:03:00 Creating a GeoDjango Application Skeleton 00:10:00 Section 04: Writing the GeoDjango Back-end Code Adding a Spatial Database to our Django Backend 00:09:00 Updating our django models file 00:08:00 Registering our model in the admin file Part1 00:09:00 Registering our model in the admin file Part2 00:10:00 Registering our model in the admin file Part3 00:10:00 Section 05: Building the Front-End using Leaflet.js Updating the settings file 00:07:00 Creating the layout page Part 1 00:09:00 Creating the layout page Part 2 00:10:00 Creating the layout page Part 3 00:07:00 Creating the index page Part 1 00:10:00 Creating the index page Part 2 00:07:00 Updating the index page 00:07:00 Section 06: Adding the Data Creating datasets 00:10:00 Displaying data on the map Part 1 00:10:00 Displaying data on the map Part 2 00:02:00 Creating a legend 00:10:00 Creating the barchart legend 00:06:00 Creating the barchart Part 1 00:10:00 Creating the barchart Part 2 00:09:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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Duration 4 Days 24 CPD hours This course is intended for The App Maker builds solutions to simplify, automate, and transform tasks and processes for themselves and their team where they have deep expertise in the solution business domain. They have basic data modeling, user experience design, requirements analysis, and process analysis skills. The App Maker creates and enforces business processes, structures digital collection of information, improves efficiency of repeatable tasks, and automates business processes. The App Maker uses the Maker tools of Power Platform to solve business problems. They may use advanced features of Microsoft apps and third-party productivity tools. The App Maker is aware of the capabilities and limitations of available tools and understands how to apply them. The App Maker is self-directed, and solution focused. They may not have formal IT training but are comfortable using technology to solve business problems with a personal growth mindset. They understand the operational need and have a vision of the desired outcome. They approach problems with phased and iterative strategies. This course will teach you how to build apps with low-code techniques to simplify, automate, and transform business tasks and processes using Microsoft Power Platform. This course contains a 1-day Applied Workshop. This workshop will allow you to practice your App Maker skills by creating an end-to-end solution to solve a problem for a fictitious company. The solution will include a Microsoft Dataverse database, Power Apps canvas app, and Power Automate flows. 1 - Get started with Microsoft Power Platform for app makers Identify components Create apps Get started with Microsoft Dataverse Work with Copilot in Microsoft Power Platform 2 - Create tables in Dataverse Table characteristics Table relationships Dataverse logic and security Dataverse auditing Dual-write vs. virtual tables 3 - Create and manage columns within a table in Dataverse Define columns in Microsoft Dataverse Column types in Microsoft Dataverse Add a column to a table Primary name column Restrictions that apply to columns in a table Create an auto numbering column Create an alternate key 4 - Load/export data and create data views in Dataverse View data in a table Create or edit views of data in a table Dataverse data import options Load data into a table Dataverse data export options Export Add, update, or delete data in a table by using Excel Import data using Power Query 5 - Export data from Dataverse and use Microsoft Excel to edit records Export data to Excel Edit and update data in Excel 6 - Get started with Microsoft Dataverse for Teams Dataverse for Teams vs Dataverse Provision your first Dataverse environment Create your first table to store data 7 - Build your first app with Power Apps and Dataverse for Teams Create your first app with the hero template Customize your app with Power Apps Studio Publish your app Install template apps 8 - Build your first workflow with Power Automate and Dataverse for Teams Types of workflows that Power Automate can build in Dataverse Schedule a flow 9 - Create reports with Power BI and Dataverse for Teams Connect to and transform Dataverse for Teams data from Power BI Create a Power BI report Publish the report Share the data 10 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 11 - Explore what Power BI can do for you What can I do with the Power BI service as a consumer? View content in the Power BI service Collaborate and share in Power BI Find and view dashboards and reports 12 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 13 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 14 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 15 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method 16 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 17 - Secure, publish, and share data in Power BI Share and use reports in Power BI Row-level security Publish a report to a Power BI workspace Share reports and user experience Protect data in Power BI Data refresh and alerts 18 - Embed Power BI content Embed Power BI reports Embed other Power BI content types Optimize the embedding experience 19 - How to build your first model-driven app with Dataverse Model-driven apps, powered by Microsoft Dataverse Explore sample apps 20 - Get started with model-driven apps in Power Apps Introducing model-driven apps Components of model-driven apps Design model-driven apps Incorporate business process flows 21 - Configure forms, charts, and dashboards in model-driven apps Forms overview Form elements Configure multiple forms Use specialized form components Configure views overview Configure grids Create and edit views Configure charts overview Dashboards overview Use interactive streams and tiles 22 - Manage Dynamics 365 model-driven app settings and security Configure role-based security Manage teams and business units Explore settings and customizations 23 - Use specialized components in a model-driven form Create business process flows Embed a canvas app in a model-driven form Add a timeline in a model-driven form Create a report in a model-driven form 24 - Get started with Power Apps canvas apps Start Power Apps Power Apps data sources Use Power Apps with Power Automate and Power BI Designing a Power Apps app 25 - Customize a canvas app in Power Apps Improve your app by making basic customizations Explore controls and screens in canvas apps 26 - How to build the User Interface in a canvas app in Power Apps Use themes to quickly change the appearance of your app Brand a control Icons Images Personalization Build for phones or tablets 27 - Navigation in a canvas app in Power Apps Understanding navigation The Navigate and Back functions More ways to use the Navigate function 28 - Manage apps in Power Apps Power Apps review 29 - Build a mobile-optimized app from Power Apps Learn about mobile-optimized apps Identify components to make a canvas app mobile-optimized Create a mobile-optimized app that uses responsive designs Identify performance considerations for a mobile-optimized canvas app 30 - Use and understand Controls in a canvas app in Power Apps Core properties of controls Entering and displaying data with text controls Additional controls for enhancing your app's usability Media Modern controls Work with component libraries 31 - Create formulas to change properties in a Power Apps canvas app Formulas overview Use a formula to modify the format of controls Use formulas to perform calculations Use a control to modify the property of other controls Conditional formatting Functions for validating data 32 - Use imperative development techniques for canvas apps in Power Apps Imperative versus declarative development The three types of variables in Power Apps Global variables Contextual variables Collections Additional variable concepts 33 - Manage apps in Power Apps Power Apps review 34 - Create formulas to change properties in a Power Apps canvas app Formulas overview Use a formula to modify the format of controls Use formulas to perform calculations Use a control to modify the property of other controls Conditional formatting Functions for validating data 35 - Create formulas to change behaviors in a Power Apps canvas app Formulas and functionality Understanding true and false Understanding control behaviors and actions Performing multiple actions in a formula Control the display mode through a formula Use controls and functions to create a dynamic formula 36 - Author a basic formula that uses tables and records in a Power Apps canvas app Records and tables Using the Table function Store a table Filter your table Use the lookup function to return a record Additional table functions 37 - Build a canvas app for a real estate solution with Copilot in Power Apps 38 - Get started with Power Automate Introducing Power Automate Create your first flow Troubleshoot flows 39 - Build approval flows with Power Automate Provide solutions to real-world scenarios. 40 - Build flows to manage user information 41 - Power Automate's deep integration across multiple data sources 42 - Use the Admin center to manage environments and data policies in Power Automate Administer flows Export and import flows Learn how to distribute button flows 43 - Use AI Builder in Power Automate AI Builder in Power Automate saves time Advanced usage of AI Builder in Power Automate 44 - Optimize your business process with process advisor Get familiar with process advisor Create your first recording Edit recordings and group actions Analyze recordings and interpret results Automation recommendations 45 - Optimize your business process with process advisor Get familiar with process advisor Create your first recording Edit recordings and group actions Analyze recordings and interpret results Automation recommendations 46 - Build flows for a real estate solution using Copilot in Power Automate When to use Copilot in Power Automate 47 - Use Dataverse triggers and actions in Power Automate Dataverse triggers Query data Create, update, delete, and relate actions 48 - Create tables in Dataverse Table characteristics Table relationships Dataverse logic and security Dataverse auditing Dual-write vs. virtual tables 49 - Create and manage columns within a table in Dataverse Define columns in Microsoft Dataverse Column types in Microsoft Dataverse Add a column to a table Primary name column Restrictions that apply to columns in a table Create an auto numbering column Create an alternate key 50 - Get started with Power Apps canvas apps Start Power Apps Power Apps data sources Use Power Apps with Power Automate and Power BI Designing a Power Apps app 51 - How to build the User Interface in a canvas app in Power Apps Use themes to quickly change the appearance of your app Brand a control Icons Images Personalization Build for phones or tablets 52 - Get started with Power Automate Introducing Power Automate Create your first flow Troubleshoot flows 53 - Challenge Project - Build a booking requests app with Power Apps and Power Automate Prepare

Build real-world MVC applications using Repository Pattern, N-Tier Architecture, APIs, Entity Framework Core and ASP.NET MVC Core 3.1