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Overview This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning for Predictive Maps in Python and Leaflet is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 9 sections • 33 lectures • 05:59:00 total length •Introduction: 00:10:00 •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 •Adding the settings.py Code: 00:07:00 •Creating a Django Model: 00:10:00 •Adding the admin.py Code: 00:21:00 •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 •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 •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 •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 •Resource: 00:00:00 •Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00
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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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