Data visualization is one of the most important parts of data analysis and an integral piece of the whole data science process. It not only enables the communication of results, it also serves to explore and understand data better. For this reason, data visualization is a necessary part of the toolkit for anyone working in data science.
This course focuses on data visualization goals, main assumptions, and techniques. We explain a variety of approaches to compare data, find relationships, follow data evolution over time, detect outliers, and reduce dimensionality. We conclude with creating interactive dashboards and showing how to share them via a web browser.
This is an external instructor-led course consisting of four, 75-minute online sessions run by Barbora Stetinova and one of our KNIME data scientists. Along with the teaching time, each session has an exercise for you to complete at home. The course concludes with a 15-minute wrap-up session.
- Session 1: Why visualization?
- Session 2: Comparing data and their development over time
- Session 3: Finding outliers and reducing dimensionality
- Session 4: Creating interactive dashboards
- Session 5: Recap, final exercise, and Q&A
If you are interested in signing up: