Course Description
Advanced Data Visualization is a comprehensive course that focuses on teaching learners how to create visually compelling and informative data visualizations using three popular Python libraries: Matplotlib, Plotly, and Seaborn. These libraries offer a wide range of tools and functionalities for creating static, interactive, and statistical visualizations. The course covers various aspects of data visualization to effectively communicate insights and patterns in data.
Advanced Visualization Techniques using Matplotlib, Plotly, and Seaborn Libraries
This module will cover the following topics:
Working with advanced plot types: 3D plots, polar plots, etc.
Creating interactive plots, dashboards, and animations
Customizing interactivity and adding annotations
Advanced statistical plotting.
Customizing plot appearance: colors, labels, titles, legends, etc.
Geographic Data Visualization
This module will cover the following topics:
Plotting geographical data
Plotting geographical maps using libraries like Basemap or Folium
Customizing maps and adding overlays
Visualizing geospatial patterns and relationships
Annotations and text placement on maps
Dashboarding and Interactive Visualization
This module will cover the following topics:
Building interactive dashboards using libraries like Plotly
Building interactive dashboards using libraries like Dash
Building interactive dashboards using libraries like Bokeh
Creating interactive widgets and controls
Linking visualizations and creating dynamic interactions
Styling and Aesthetics
This module will cover the following topics:
Enhancing visualizations with appropriate colors, fonts, and styles
Creating visually appealing and informative data visualizations
Design principles for effective data communication
Importance of data visualization in data analysis
Principles of effective data visualization
Course Achievements
Throughout the course, learners will have hands-on practice with real-world datasets, engaging in exercises and projects to create meaningful visualizations. They will gain practical skills in data visualization using Matplotlib, Plotly, and Seaborn, enabling them to present data in visually compelling and informative ways.
Deep understanding of data visualization techniques
Deep understanding of data visualization best practices
Creating static visualizations
Creating interactive visualizations
