📊 Introduction to Statistical Learning in R

Table of Contents


This course offers an introduction to statistics and supervised machine learning. It adopts a problem-to-solution teaching approach, defining a practical problem and illustrating how statistics can enable understanding to make critically informed decisions about a population by examining a random sample. It uses a learning-by-doing approach based on real-world examples in various contexts. This also teaches how to conduct statistical data analysis in R. The course is organised around 6 sessions. Each session is designed to provide a combination of key statistical concepts and practical application through the use of R.

Learning outcomes

Having successfully completed this course, you will be able to:

  • Conduct exploratory statistical data analysis.
  • Have an understanding of elementary probability distributions and data types.
  • Perform correlation and regression data analysis using real-world data.
  • Assess the statistical significance between different data types.
  • Carry out statistical data analysis in R.
  • Have a basic understanding of supervised machine learning and cross-validation.


The notes for each session are:

Meet your instructor

Francisco Rowe