Learn how to build full stack web-GIS apps, predictive models, integrate postgreSQL with Django and visualise data on maps.

Course Description

Welcome to the Machine Learning for Predictive Maps in Python and Leaflet course. In this course we will be building a earthquake forecasting map application, by using a variety of independent tools and then integrate them to produce a full stack web gis application. We will be writing code in multiple programming languages, which gives us experience with different stacks of an application and different tools. We will be covering various topics ranging from web gis, python programming, data analysis, machine learning and geo data visualisation. All of our development will be done on windows 10.
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Machine learning

Course curriculum

  1. 01
  2. 02
  3. 03

    • Lesson 7: Adding the settings.py Code

    • Lesson 8: Creating a Django Model

    • Lesson 9: Adding the admin.py Code
  4. 04

    • Lesson 10: Creating Template Files

    • Lesson 11: Creating Django Views

    • Lesson 12: Creating URL Patterns for the REST API

    • Lesson 13: Adding the index.html code

    • Lesson 14: Adding the layout.html code

    • Lesson 15: Creating our First Map

    • Lesson 16: Adding Markers
  5. 05
  6. 06

    • Lesson 21: Creating a Django Model

    • Lesson 22: Embedding the Machine Learning Pipeline in the Application

    • Lesson 23: Creating a URL Endpoint for our Prediction Dataset
  7. 07

    • Lesson 24: Creating Multiple Basemaps

    • Lesson 25: Creating the Marker Layer Group

    • Lesson 26: Creating the Point Layer Group

    • Lesson 27: Creating the Predicted Point Layer Group

    • Lesson 28: Creating the Predicted High Risk Point Layer Group

    • Lesson 29: Creating the Legend

    • Lesson 30: Creating the Prediction Score Legend
  8. 08

    • Source code and Notebook

Some of the skills you will acquire from taking this course are:

  • You will learn how to build a full stack web gis application

  • You will learn how to build predictive models

  • You will learn how to build a prediction engine that's embedded in the application

  • You will learn how to build and automate a machine learning pipeline

  • You will learn how to use multiple bases-maps and layers

  • You will learn programming in leaflet.js

  • You will learn how to create REST API endpoints and call them with Ajax and JQUERY

  • You will learn how to use the Django template engine to pass data from the backend to the frontend of the application

  • You will learn how to integrate a postgresql database with Django

  • You will also learn how to visualise data on a map

Student Profile?

  • Under/post graduate students

  • Professionals and Companies

  • Master students and PhD candidates

  • Researchers and Academics

Some more information

  • Certificates of Completion

    After you successfully finish the course, you can claim your Certificate of Completion with NO extra cost! You can add it to your CV, LinkedIn profile etc

  • Available at any time! Study at your best time

    We know hard it is to acquire new skills. All our courses are self paced.

  • Online and always accessible

    Even when you finish the course and you get your certificate, you will still have access to course contents! Every time an Instructor makes an update you will be notified and be able to watch it for FREE

About your Instructor

Data Engineer and business intelligence consultant with an academic background in Bsc computer science and around 5 years of experience in IT. Involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. My career started as an embedded software engineer writing firmware for integrated microchips, then moved on as an ERDAS APOLLO developer at geo data design a hexagon geospatial partner. Am now a consultant at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies I use to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.

Edwin Bomela

Data Engineer and business intelligence consultant

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