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Spatial Data Visualisation and Machine Learning in Python

(2 students)

This course includes:

04:40:00 hours

CPD Accreditation

20 units

Full lifetime access

Access on mobile and TV

Certificate of completion

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Key Concepts Covered by This Free Course

  • Develop proficiency in setting up and installing Python for data analysis.
  • Understand and apply various techniques for data preparation and cleaning.
  • Gain expertise in creating effective data visualizations to communicate insights.
  • Acquire knowledge of machine learning algorithms and their implementation in Python.
  • Build an interactive dashboard that incorporates machine learning models and visualizations.
  • Gain hands-on experience in creating a web server to deploy and share your dashboard.

Course Overview

This course is designed for those who want to develop skills in spatial data visualization and machine learning in Python. In this course, you will learn the fundamentals of Python programming, data analysis, and visualization. You will explore machine learning algorithms and their implementation in Python. You will also learn how to create an interactive dashboard that incorporates visualizations and machine learning models. By the end of this course, you will be able to confidently create data visualizations, develop machine learning models, and build interactive dashboards to communicate insights. You will also have the skills to set up a web server to deploy and share your dashboard with others.

Course Benefits

This course will provide you with the skills to work with spatial data visualization and machine learning in Python. You will gain hands-on experience in Python programming, data analysis, and visualization. You will learn how to build effective machine learning models and create interactive dashboards that incorporate visualizations and machine learning models. Upon completion of this course, you will be able to confidently work with Python, develop machine learning models, and build interactive dashboards. These skills are in high demand in various industries such as finance, healthcare, and tech.

Career Path

  • Data Scientist - Utilize machine learning algorithms to extract insights from data.
  • Data Analyst - Analyze and interpret data using statistical methods and tools.
  • Business Analyst - Use data to make strategic decisions for an organization.
  • Machine Learning Engineer - Build and deploy machine learning models.
  • Data Engineer - Design and implement data systems and pipelines.
  • GIS Analyst - Work with spatial data to analyze and visualize geographic patterns.

Course content

Section 01: Introduction

Introduction

00:14:00

Python Installation

00:03:00

Installing Bokeh

00:04:00

Data Preparation

00:24:00

Creating a Bar Chart

00:18:00

Creating a Line Chart

00:12:00

Creating a Doughnut Chart

00:22:00

Creating a Magnitude Plot

00:31:00

Creating a Geo Map Plot

00:20:00

Creating a Grid Plot

00:12:00

Data Pre-processing

00:21:00

Building a Predictive Model

00:21:00

Building a Prediction Dataset

00:07:00

Adding predicted data to our plots – Part 1

00:13:00

Adding predicted data to our plots – Part 2

00:14:00

Adding predicted data to our plots – Part 3

00:15:00

Adding the Grid Plot

00:08:00

Installing Visual Studio Code

00:01:00

Creating the Project and Virtual Environment

00:08:00

Building and Running the Server

00:12:00

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