Data Science with R Programming

180h

Week 1-2: Introduction to R programming

Introduction to R language and RStudio IDE

Data types and structures, operators, and basic functions

Data input/output, packages, and help documentation

Exploratory data analysis (EDA) with base R functions and ggplot2

Week 3-4: Data manipulation and visualization with tidyverse

Week 5-6: Statistical analysis and machine learning with caret

Week 7-8: Data modeling and visualization with ggplot2

Week 9-10: Time series analysis and forecasting

Week 11-12: Advanced topics and project work

About Course

Data Science is a field that involves using statistical and computational techniques to extract insights and knowledge from data. R is a programming language widely used in Data Science for statistical computing and graphics. In this context, using R for Data Science is a popular choice among data analysts, data scientists, and researchers.

R provides a variety of packages and libraries for statistical analysis, data manipulation, visualization, and machine learning. Some popular libraries for data analysis in R include dplyr, tidyr, and ggplot2. Machine learning libraries such as caret, randomForest, and xgboost can also be used to build predictive models.