Basics
Introduction to R
- What is R?
- Setting up R environment
- Basic syntax and structure
- Basic data types and structures
Data Manipulation
- Vectors and lists
- Data frames and matrices
- Factors
- Subsetting data
Basic Functions
- Creating and using functions
- Control structures (if, else, for, while)
- Apply family of functions
Data Visualization
- Base graphics
- ggplot2 basics
- Creating plots
Intermediate
Data Cleaning
- Handling missing values
- Data transformation with dplyr
- String manipulation with stringr
Data Import and Export
- Reading data from files
- Writing data to files
- Working with databases
Statistical Analysis
- Descriptive statistics
- Hypothesis testing
- Linear regression
- ANOVA
Working with Dates and Times
- Date and time classes
- Formatting dates and times
- Calculating differences
Advanced
Advanced Data Visualization
- Advanced ggplot2 techniques
- Interactive plots with plotly
- Creating dashboards with Shiny
Machine Learning
- Introduction to machine learning in R
- Supervised learning
- Unsupervised learning
- Model evaluation
Parallel Computing
- Introduction to parallel computing
- Using parallel package
- Optimizing code for parallel execution
Package Development
- Creating your own package
- Documenting your package
- Submitting to CRAN