Data visualization

In our data-driven world, the ability to visualize information clearly and compellingly is crucial. Modern data visualization techniques transform complex datasets into visually appealing insights. Yet, crafting high-quality visualizations that truly resonate with your audience can be a daunting task, fraught with challenges such as:

• Setting up the right environments
• Selecting the appropriate visual elements
• Mastering various tools
• Writing effective code
• Creating publication-ready visuals

Content and learning goals of the course:

This course is designed to immerse you in the world of data visualization, equipping you with the skills to turn data into stunning, insightful visuals. What You'll Learn:

• Data Handling for Visualizations: Learn the essentials of managing and preparing data for visualization.
• Visualization Techniques: Explore and implement a range of popular visualization methods commonly used in scientific research.
• Perception in Visualization: Understand key perception principles to ensure your visualizations are intuitive and impactful.
• Design Principles: Dive into the fundamentals of effective visualization design.

Throughout the course, you'll engage with real-world use cases, designing compelling visualizations to address specific problems and scenarios.

Tools and Technologies:

• Tableau: Master this powerful drag-and-drop tool to create interactive charts, including bar and scatter plots, maps, heat maps, and tree maps.
• Python and R Notebooks: For other visualization techniques like violin plots, parallel coordinates and projections, you'll learn to leverage the capabilities of Python and R to build insightful  visualizations.
• JupyterLab: Utilize this versatile development environment to create, share, and experiment with code and visualizations seamlessly.

Prerequisites:

Basic Python or R skills are helpful but not strictly necessary.

Course dates:

The course consists of six 2-hour sessions (15:00 to 17:00), which are all within 2 weeks:

• October course: Oct 7, 10, 11, 14, 16, 18
• February course: Feb 3, 5, 7, 10, 12, 14
• May course: May 19, 21, 23, 26, 28, 30

Join us on this journey to increase your data visualization skills, making your insights not just seen, but understood and appreciated by your audience.

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