Course Content
Introduction to R and Data Science
0/2
Overview of R Programming
Data Science Workflow with R
Data Structures and Manipulation
0/3
Vectors, Lists, and Matrices
Data Frames and Tibbles
Data Import and Export
Data Wrangling and Cleaning
0/3
Data Cleaning with dplyr
Handling Missing and Outlier Data
Data Reshaping with tidyr
Data Visualization with R
0/3
Introduction to ggplot2
Customizing Visualizations
Advanced Data Visualization
Statistical Analysis in R
0/3
Descriptive Statistics
Inferential Statistics
Correlation and Regression Analysis
Machine Learning with R
0/4
Introduction to Machine Learning
Supervised Learning
Unsupervised Learning
Model Optimization and Tuning
Time-Series Analysis
0/2
Basics of Time-Series Data
Time-Series Forecasting
Big Data and R in Production
0/3
Working with Big Data
Web Scraping and APIs
Automating Reports and Dashboards
Real-World Case Studies
0/3
Case Study: Customer Churn Prediction
Case Study: Stock Market Analysis
Case Study: Social Media Sentiment Analysis
Capstone Project
R Programming for Data Science
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