Home / R programming language

- Overview of R and its features
- Installation and setup of R
- Introduction to RStudio and the R environment

- Importing and exporting data in R
- Data cleaning and preprocessing
- Working with missing values and outliers

- Summarizing and visualizing data in R
- Descriptive statistics and data distributions
- Creating plots, charts, and graphs

- Advanced data visualization techniques
- Customizing plots and adding annotations
- Creating interactive visualizations

- Hypothesis testing and statistical inference
- Parametric and non-parametric tests in R
- Regression analysis and model building

- Introduction to the dplyr and tidyr packages
- Manipulating and transforming data frames
- Grouping, aggregating, and summarizing data

- Introduction to machine learning algorithms in R
- Supervised learning (classification, regression)
- Unsupervised learning (clustering, dimensionality reduction)

- Analyzing text data in R
- Text preprocessing and tokenization
- Sentiment analysis and text classification

- Working with time series data in R
- Time series decomposition and forecasting
- Seasonality and trend analysis

- Exploring popular R packages (ggplot2, dplyr, etc.)
- Using external libraries for specific tasks
- Creating and sharing R packages

- Creating dynamic reports and documents with R Markdown
- Combining code, text, and visualizations
- Generating HTML, PDF, and Word documents

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