This course provides a hands-on introduction to data science using the R programming language. Students will learn to clean, manipulate, analyze, visualize, and model data using real-world datasets. The course covers the full data science workflow, with emphasis on reproducibility, communication, and practical implementation using R’s rich ecosystem of packages.
Data Science with R is designed for learners who want to gain foundational and intermediate skills in data analysis, visualization, and machine learning using R. The course combines statistical theory with hands-on coding exercises to help students develop practical skills in working with data.
Through real-world projects and case studies, learners will explore techniques to draw meaningful insights, create compelling visualizations, build predictive models, and present results in reproducible reports and interactive dashboards.
Whether you're a student, analyst, researcher, or professional looking to switch to a data-driven career, this course gives you the tools you need to analyze and communicate data effectively using R.
Use R for importing, cleaning, and transforming data
Create effective data visualizations
Apply statistical and machine learning models to real-world datasets
Interpret and communicate data insights clearly and accurately
Develop reproducible workflows and interactive data products
Introduction to
R and RStudio
Data manipulation with
dplyr and tidyr
Data visualization
with ggplot2
Exploratory data
analysis (EDA)
Statistical modeling
and inference
Machine learning algorithms (regression, classification, clustering)
Time series analysis (optional/advanced)
Reporting with
R Markdown
Interactive dashboards
using Shiny
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Ideal for fast-paced learning with daily live sessions and hands-on projects
Suitable for working professionals or students balancing other commitments
Suitable for working professionals or students balancing other commitments
Suitable for working professionals or students balancing other commitments
Whether you're aspiring to become a full-stack developer, looking to enhance your career, or build your own end-to-end applications, this
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