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Course Outline
Introduction to Google Colab for Visualization
- Overview of Google Colab
- Setting up Google Colab
- Navigating the Google Colab interface
Getting Started with Data Visualization
- Importance of data visualization
- Introduction to Python visualization libraries
Basic Plotting with Matplotlib
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Creating simple plots
- Line plots
- Bar charts
- Pie charts
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Customizing plots
- Titles, labels, and legends
- Colors, styles, and themes
Advanced Plotting with Matplotlib
- Subplots and multiple plots
- Working with annotations
- Saving and exporting plots
Introduction to Seaborn
- Overview of Seaborn
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Creating statistical plots
- Distribution plots
- Regression plots
- Categorical plots
Customizing Seaborn Plots
- Aesthetics and themes
- Advanced customizations
- Combining Seaborn with Matplotlib
Handling and Visualizing Real-world Datasets
- Importing datasets
- Cleaning and preparing data
- Visualizing complex data
Collaborative Visualization Projects
- Sharing and collaborating on notebooks
- Real-time collaboration features
- Best practices for collaborative projects
Tips and Best Practices
- Effective data visualization techniques
- Avoiding common visualization pitfalls
- Enhancing visual appeal and clarity
Summary and Next Steps
Requirements
- Basic knowledge of Python programming
- Familiarity with basic data concepts
Audience
- Data scientists
- Data professionals
14 Hours
Testimonials (1)
Real world knowledge from someone in the industry