Data Science Tutorial with R
Last Updated :
23 Jul, 2025
Data Science is a field that combines statistics, computer science and subject knowledge to find useful insights from both organized and unorganized data, helping turn information into practical decisions. In this tutorial, we will explore how the data science process is implemented in an R console or R studio, covering essential concepts, tools and techniques commonly used in the field.
Installation of R
In this section, we will explore about R programming language , installing of R and RStudio.
Basic Understanding of R
In this section, we will cover the basic concepts and syntax of R programming. This will include understanding variables, data types and basic operations that form the foundation of programming in R.
Data Preprocessing in R
In this section, we will explore how to preprocess data in R by handling missing values, converting data types and preparing datasets for analysis.
Data Analysis with R
In this section, we will introduce basic data analysis techniques to extract insights from datasets.
Statistical Analysis in R
Statistical analysis is helps in understanding data and making data-driven decisions. R offers a wide range of functions for both descriptive and inferential statistics.
1. Descriptive Statistics
2. Inferential Statistics
3. Multivariate Tests in R
4. Time Series Analysis in R
Data Visualization in R
Data visualization helps in understanding and communicating data insights effectively. R provides powerful tools like ggplot2 for creating professional visualizations.
Machine Learning in R
Machine learning focuses on developing algorithms that helps computers to learn from data and make predictions or decisions without explicit programming.. R provides extensive support for both supervised and unsupervised learning algorithms.
Deep Learning in R
Deep learning is a subset of machine learning using neural networks to learn from large datasets and make complex predictions. R supports deep learning through packages like keras, tensorflow and torch, enabling easy model building and training.
Data Science with R is a comprehensive approach to tackling a wide range of problems. By combining statistical analysis, data visualization and machine learning, R enables data scientists to gain deep insights from data.
To get a detailed overview of R programming, you can refer to: R Programming Tutorial
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