Supervised-Learning-and-Visualization 2022 @ Utrehct University

This repository contains all practicals and assignments for the Supervised Learning and Visualization course.

Course Description:

At the end of this course, students are able to apply and interpret the theories, principles, methods and techniques related to contemporary data science, and understand and explain different approaches to data analysis:

This course provides a broad introduction to supervised learning and visualization. Topics include:

• Data manipulation and data wrangling with R.
• Data visualization.
• Exploratory data analysis.
• Regression and classification.
• Non-linear modeling.
• Bagging, boosting, and ensemble learning.