Machine Learning for Predictive Maps in Python and Leaflet

Master predictive mapping and geospatial analysis in this Machine Learning Course for £29.99. Learn Python, Leaflet, and automation with CPD certification

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Course Overview

Learn predictive analytics and geospatial mapping with our Machine Learning for Predictive Maps in Python and Leaflet course. This machine learning course combines Python programming, machine learning techniques, and interactive mapping to prepare you for a career in data science and GIS.

Whether you are a beginner or a professional, this course offers lifetime access to resources & CPD certification. These features help you gain skills that are applicable to real-world challenges and advance your career.

Description

The Machine Learning for Predictive Maps in Python and Leaflet course blends theory with hands-on practice. Each section is carefully designed to ensure you gain expertise and a deep understanding of machine learning and geospatial mapping

What You’ll Learn:

Who Is This Machine Learning Course Course For?

This course is ideal for:

Aspiring Data Scientists: Build a strong foundation in machine learning and Python.
IT Professionals: Upgrade your skills in predictive analytics and application development.
GIS Enthusiasts: Learn how to create interactive geospatial maps.
Beginners and Students: Start your journey in data science with no prior experience required.

Certificate of Achievement

Upon completion, you will receive a CPD Accredited Certificate recognised globally. You can choose the format that suits you best:

PDF Certificate: Only £2.99.
Hard Copy Certificate: Only £8.99.

This credential validates your expertise and enhances your professional profile.

Requirements For Machine Learning Course

To enrol in thiscourse, all you need is:

Career Path

This machine learning course course equips you with the skills needed to excel in roles such as:

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