Large Scale Data Analysis and Visualization

This course teaches students principles of scientific visualization of data using the R and Python programming languages. Starting from introductory large scale data handling and basics of visualization, more advanced methods for visualization will also be covered. Important libraries and frameworks that are essential for data analysis and visualization are introduced.

On completion of the course, students should be familiar with libraries in the R and Python programming languages that enable them to create professional scientific visualizations. This outcome includes the application of those scientific libraries, handling of large datasets and knowledge of many examples of how challenges in scientific visualization were overcome and in what ways creative solutions were found.

Skills:

• Knowledge on how to include scientific visualization in research projects
• Independent choice of ways to prepare large scale data to run visualization methods to solve a given problem
• Knowledge about different libraries and their (dis-)advantages
• Data preprocessing, analysis, organisation and visualization

Necessary:  –

Recommended: Basic knowledge about statistics and 1) either basic knowledge of R and Python or 2) intermediate knowledge of either Python or R and willingness to learn the other, yet unfamiliar language