The main goal of this lesson is to demonstrate the importance of data visualization and how it can unlock a variety of learning and research pathways—ranging from exploratory data analysis and statistical inference to understanding machine learning processes and data storytelling.
If you're looking for ways to approximately predict specific values based on a given dataset for data storytelling, or if you've ever wondered how machine learning models that predict values (rather than categories) work, this lesson is for you. It will introduce you to the concept of statistical inference—a mathematical calculation used in predictive machine learning algorithms—through various data visualization techniques. These visualization methods will also enhance your data storytelling skills, not only in describing existing data but also in predicting values based on the available data.
Data visualization is central to this lesson, serving as both the means and the goal. You’ll not only learn to write Python code and engage in hands-on data visualization, but also discover how to explore, understand, and predict dataset values through visualization techniques.
This lesson has been developed by Golnaz Sarkar Farshi.
This lesson has been developed as part of the joint project HERMES – Humanities Education in Research, Data, and Methods. HERMES is funded by the German Federal Ministry of Education and Research (BMBF) through grants from the European Union.
This lesson has a CC-BY license.