PROGRAMMING WITH R (4 DAYS)
TARGET AUDIENCE
Data analysts, statisticians, and researchers interested in using R for data manipulation.
DESCRIPTION
4-DAY COURSE
This provides a comprehensive introduction to the R programming language, covering data analysis, visualization, and statistical modelling.

LEARNING OUTCOMES
- Introduction to R: Understand the basics of the R programming language, including its syntax, data structures (vectors, matrices, data frames), and built-in functions.
- Data Import and Export: Learn how to import data into R from various sources such as text files, CSV files, Excel spreadsheets, databases, and web APIs, and export data to different formats.
- Data Manipulation: Master data manipulation techniques in R using packages like dplyr and tidyr, including filtering, sorting, summarizing, grouping, and reshaping data.
- Data Visualization: Explore data visualization capabilities in R using packages like ggplot2, including creating scatter plots, bar charts, histograms, box plots, and heatmaps.
- Statistical Analysis: Understand statistical analysis techniques in R, including descriptive statistics, hypothesis testing, regression analysis, ANOVA, and chi-square tests.
- Time Series Analysis: Learn about time series analysis and forecasting techniques in R, including time series decomposition, ARIMA modeling, and exponential smoothing methods.
- Interactive Dashboards: Learn how to create interactive dashboards and web applications in R using Shiny, allowing for dynamic data visualization and exploration.
- Reproducible Research: Explore principles and tools for reproducible research in R, including literate programming with R Markdown, version control with Git, and project organization with RStudio Projects.
By completing this course, you will have a basic understandng in using R for data analysis, visualization, and statistical modeling, enabling you to tackle real-world data challenges and derive actionable insights from data. Upon successfully completing the course, you will be awarded a certificate and a digital badge.
PREREQUISITES
Basic understanding of programming concepts and familiarity with statistical principles.
