Visualization & Business Analytics LabGSDS @ Seoul National University

Data visualization is a powerful technique for supporting decision-making, particularly in medical applications where the size and complexity of data have grown rapidly in recent years due to the advancement of the computing capabilities.

This course provides an exhaustive overview of data visualization techniques, ranging from foundational charting methods to intricate, interactive visualizations.

Utilizing Python and JavaScript as the core programming tools, the course emphasizes hands-on experience with the Medical Information Mart for Intensive Case (MIMIC) datasets, allowing students to engage with real-world medical data and cloud computing experience.

The course is structured to include a blend of lectures and a culminating group project. The group project mandates the creation of an interactive, web-based data visualization application focused on medical applications, thereby offering students an opportunity to apply theoretical knowledge to practical challenges in medical applications.

By the end of the course, students will have acquired the skills to manipulate large medical datasets and create insightful visualizations that can significantly contribute to medical research and clinical decision-making.

This course introduces exploratory data analysis and data visualization methods for a rich understanding of the data and finding insights as a preliminary step before advanced data analysis.

Students will learn the grammar of graph principles, various visualization approaches and interactive graph.

Summary Statistics ▪ Grammar of Graph Principles ▪ Data Wrangling ▪ Visualization of Relationships (correlation, time series, causation) ▪ Visualization of Multivariate Data ▪ Time Series of Dynamic Graph ▪ Visualization of Unstructured Data ▪ Interactive Graph (using shiny)