We, as one of the leading eLearning service providers across the globe, strive to provide all our learners with the best eLearning experience possible that can make a real difference in their career progression. 

• 5+ hours of video lectures and digital resources are available on demand.
• Learn at your own speed with affordable, high-quality E-learning content. 
• When you finish the course, you will be given a certificate of completion.
• Enhance your resume from a globally recognised Accredited Qualification.
• You’ll discover how effective salespeople use a researched and proven technique to boost their careers.
• You’ll be able to successfully implement several practical sales strategies and have a deeper understanding of your consumers.

This Machine Learning for Predictive Maps in Python and Leaflet course is beneficial for a wide range of learners. It is especially suitable for the following learners:

• Data scientists and analysts: Individuals seeking to broaden their expertise in predictive modelling and spatial analysis
• Professionals in Geographic Information Systems (GIS): Looking to incorporate machine learning into their workflows for mapping and spatial analysis
• Developers and Programmers: keen on integrating predictive mapping into their projects or applications.
• Urban Planners and Environmental Researchers: Investigating predictive mapping in the fields of planning, sustainability, and environmental impact
• Logistics and Supply Chain Analysts: Using predictive mapping to optimise routes and manage supply chains
• Pupils studying geography or computer science: Interested in finding out how machine learning and cartography are combining
• Decision-Making Roles Professionals: Looking for Tools and Insights to Support Strategic Decision-Making with Predictive Mapping

• Section 01: Introduction
  Introduction
• Section 02: Setup and Installations
  Python Installation
  Creating a Python Virtual Environment
  Installing Django
  Installing Visual Studio Code IDE
  Installing PostgreSQL Database Server Part 1
  Installing PostgreSQL Database Server Part 2
• Section 03: Writing the Django Server-Side Code
  Adding the settings.py Code
  Creating a Django Model
  Adding the admin.py Code
• Section 04: Writing the Application Front-end Code
  Creating Template Files
  Creating Django Views
  Creating URL Patterns for the REST API
  Adding the index.html code
  Adding the layout.html code
  Creating our First Map
  Adding Markers
• Section 05: Machine Learning
  Installing Jupyter Notebook
  Data Pre-processing
  Model Selection
  Model Evaluation and Building a Prediction Dataset
• Section 06: Automating the Machine Learning Pipeline
  Creating a Django Model
  Embedding the Machine Learning Pipeline in the Application
  Creating a URL Endpoint for our Prediction Dataset
• Section 07: Leaflet Programming
  Creating Multiple Basemaps
  Creating the Marker Layer Group
  Creating the Point Layer Group
  Creating the Predicted Point Layer Group
  Creating the Predicted High Risk Point Layer Group
  Creating the Legend
  Creating the Prediction Score Legend
• Section 08: Project Source Code
  Resource

Learners must submit a comprehensive summerised assignment on all the units that will be assessed by our expert tutor if all the learning outcomes are met as per the standard set by QLS. After the quality check, learner will be provided with the Machine Learning for Predictive Maps in Python and Leaflet certificate.

An endorsed certificate will be issued to learners at the end of the course as recognition of course completion. Provided that learner completes all the assessment of a course can claim for certificate. 

QLS endorsed this certified course as a highly qualified, non-regulated provision and training programme. There will be a trainer to answer all your questions including your progression routes into further higher education. It is a non-accredited course.

“Machine Learning for Predictive Maps in Python and Leaflet” course is relevant to many trending professions as the following:

• GIS Analyst/Developer. Salary range: £25,000 – £45,000 per year.
• Data Scientist/Spatial Analysis.Salary range: £40,000 – £70,000 per year.
• Python developer (with GIS expertise).Salary range: £35,000 – £60,000 per year.
• Machine Learning Engineer. Salary range: £50,000 – £80,000 per year.
• Urban Planner/Analyst.Salary range: £30,000 – £50,000 per year.
• Environmental Analyst/Researcher.Salary range: £25,000 – £45,000 per year.