Udemy – The Ultimate Python Data Visualization Course- Step By Step 2024-10

In this course, you will learn the basics of data visualization with Python and gradually move on to more advanced libraries such as Matplotlib, Seaborn, and Plotly. Each section of the course is designed to build on the previous section and deepen your understanding of the concepts. You will gain a solid understanding of the theoretical concepts and strengthen your practical skills by working on real-world projects and practical examples.

What you will learn:

• Python Introduction to Data Visualization: Familiarity with basic Python concepts needed for data visualization.
• Install required libraries: Install and configure powerful Python libraries such as Matplotlib, Seaborn, and Plotly.
• Basic charts: Create line, scatter, and column charts as the basis for data visualization.
• Customize charts: Add titles, labels, legends, and other elements to improve the appearance of your charts.
• Create subcharts: Display multiple charts in one image for better comparison and analysis.
• Add notes and text: Add descriptions and additional information to charts.
• Save and export charts: Save charts in various formats for use in reports and presentations.
• Customize the appearance of charts with Seaborn: Use different Seaborn themes and styles to create beautiful and attractive charts.
• Create pairwise, heatmap, and violin charts: Visually display relationships between different variables.
• Visualizing relationships with Seaborn: Show relationships between categorical, linear, and nonlinear variables.
• Create interactive charts: Build interactive line, column, and scatter charts with Plotly Dash.
• Time series data visualization: Visualizing changes in data over time.
• Performance optimization for big data: Improve the speed and efficiency of data visualization for large data sets.
• Principles of effective storytelling with data: Transforming data into engaging and understandable stories.
• Effective use of color in data visualization: Use color to highlight important information and create more attractive charts.

This course is suitable for people who:

• Interested in Python programming, Python scripting, machine learning, data science, and data visualization.
• Are interested in learning the applications of data science or data visualization.

Installation Guide

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