Data Visualization Libraries
Course Discription
This course focuses on the effective use of data visualization libraries to transform raw data into meaningful visual insights. Students will learn how to create clear, interactive, and impactful visualizations using popular Python libraries such as Matplotlib, Seaborn, Plotly, and Tableau. The course covers principles of visual design, chart selection, and storytelling with data. Learners will gain hands-on experience in building dashboards, customizing charts, and presenting analytical findings in a visually compelling manner. Real-world datasets and practical projects are used to strengthen understanding and application.
What you'll Learn
- Fundamentals of data visualization and visual storytelling
- Choosing the right chart types for different data insights
- Creating static visualizations using Matplotlib
- Designing attractive statistical plots with Seaborn
- Building interactive visualizations using Plotly
- Customizing charts (colors, labels, themes, annotations)
- Working with real-world datasets for visualization
- Best practices for data visualization and design principles
- Avoiding common visualization mistakes
Student testimonial
“Learning Matplotlib and Seaborn completely changed the way I approach data. What once was messy rows of numbers now becomes beautiful, meaningful visuals. Seaborn’s aesthetics helped me create professional plots with minimal code — perfect for both exploratory analysis and final project presentations.”
POOJA VARMA
web-developer