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
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.
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
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Enrol on the now and start learning instantly! What You Get With The Create Smart Maps in Python and Leaflet Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Create Smart Maps in Python and Leaflet, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. 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. 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The CILT Level 3 Award in Warehousing is designed to provide Learners with the knowledge and understanding of warehousing principles and to deliver the skills required by an aspiring warehouse manager to operate effectively. The qualification covers all of the key areas and activities of warehousing operations.
Build real-world MVC applications using Repository Pattern, N-Tier Architecture, APIs, Entity Framework Core and ASP.NET MVC Core 3.1
Level 5 QLS Endorsed Course | Endorsed Certificate Included | Plus 5 Career Guided Courses | CPD Accredited