Introduction to Data Science

Fundamentals of Data Science for Health and Care Using R

Summary of the course

In this course we will introduce the basic ideas of Data Science and we will implement them using the R programming language. We will use the Tidyverse, which is a collection of R packages that facilitate data import, manipulation, encoding, exploration and visualisation.

See this video for an introduction to the course, the trainers and what you will learn.

Learning outcomes

• To understand basic concepts of data science and how to implement them in R using the Tidyverse.
• To learn how to extract and communicate insights retrieved through data analysis.

Detailed Programme

Day 1: Introduction to the Tidyverse
Introduction to R and RStudio. Workflow. Tidy data. The Tidyverse ecosystem. Data import.
Tibbles. Dplyr basics. Pipes.

Day 2: Data Manipulation
Dplyr verbs. Numerical summaries. SQL and Dplyr.

Day 3: Categorical Variables
Factors. The package forcats. Modifying factor order. Modifying factors levels.

Day 4: Relational Data
Mutating joins. Filtering joins. Set operations.

Day 5: Data Visualisation I
Introduction to ggplot2. Creating a ggplot. Aesthetic mappings. Geometric objects.

Day 6: Data Visualisation II
More geometric objects. Themes.

Day 7: Exploratory Data Analysis I
Visualising distributions. Typical vs unusual values. Missing values.

Day 8: Exploratory Data Analysis II
Covariation. A categorical and continuous variable. Two categorical variables. Two continuous
variables.

Trainers

Your training will be led by:

• Filippo Cavallari, Data Science Lecturer, Data Science Campus, Office for National Statistics | Swyddfa Ystadegau Gwladol and
• Penny Holborn, Head of Faculty, Data Science Campus, Office for National Statistics | Swyddfa Ystadegau Gwladol