Courses
Regular Courses
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 advancements in 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 MIMIC datasets, allowing students to engage with real-world medical data and cloud computing environments.
The course is structured to include a blend of lectures and a culminating group project, which requires students to create an interactive, web-based data visualization application for medical applications.
By the end, students will have acquired the skills to manipulate large medical datasets and create insightful visualizations that significantly contribute to medical research and clinical decision-making.
This course introduces exploratory data analysis and visualization methods for a rich understanding of data and generating insights before advanced analysis.
Students will learn the grammar of graph principles, various visualization approaches, and interactive graphics.
Topics include: Summary Statistics, Grammar of Graph Principles, Data Wrangling, Visualization of Relationships (correlation, time series, causation), Visualization of Multivariate Data, Time Series and Dynamic Graphs, Visualization of Unstructured Data, and Interactive Graphs (using Shiny).