R Training Agenda

Day 1 – R Fundamentals

8:30

• Introduction

• R and RStudio installation

• RStudio demo

• Basic R concepts, vocabularies

• Data types

• Data structures

12:30 Lunch break

14:00

• Data import and Export

• Packages and functions

• R operators

• Common functions

• Exercises

17:00 End

Day 2 – Data Preparation for Analysis

8:30

• Recap of day 1 – Q & A

• Explore

• Subset

• Re-structure data

• Combine data

12:30 Lunch break

14:00

• Transform

• Missing Values

• Descriptive statistics

• Useful packages and functions

• Exercises

17:00 End

Day 3 – Data Visualization

8:30

• Recap of day 2 – Q & A

• Elements of Graphics

• Basic steps of data visualization (ggplot2)

• Univariate data visualization

• Bivariate data visualization

• Faceting

12:30 Lunch break

14:00

• Multivariate data visualization

• Plot styling and labeling

• Correlation visualization

• PCA and biplot

• Exercises

17:00 End

Day 4 – Data Analysis

8:30

• Recap day 3 – Q & A

• Data analysis

12:30 Lunch break

14:00

• Experiment designing

• Exercises

17:00 End

Day 5 – R programming

8:30

• Recap day 4 – Q & A

• Functional programming

• Control structures

• Loops

• Regular expressions

• Exercises

12:30 Lunch break

14:00

• Recap training themes

• Q & A

• Resources for further self-learning

17:00 End