What will you learn in Applied Data Science with R Specialization Course
Build foundational knowledge in R programming tailored for data science tasks.
Perform statistical data analysis, data wrangling, and visualization in R.
Work with real-world data using tidyverse packages and advanced visualization libraries.
Build machine learning models and understand data modeling pipelines in R.
Program Overview
Course 1: Introduction to R Programming
⏱️ 2 weeks
Topics: R syntax, data types, functions, conditionals
Hands-on: Write R scripts, use control structures, manage packages
Course 2: Data Wrangling with R
⏱️ 3 weeks
Topics: Data manipulation with
dplyr,tidyr, and data cleaningHands-on: Load, clean, transform datasets using tidyverse
Course 3: Data Visualization in R
⏱️ 3 weeks
Topics: Visualizing with
ggplot2, plot customizationHands-on: Create bar plots, histograms, scatterplots, and advanced graphics
Course 4: Machine Learning with R
⏱️ 4 weeks
Topics: Supervised and unsupervised learning, model evaluation
Hands-on: Build decision trees, random forests, and clustering models
Course 5: Data Science Capstone Project with R
⏱️ 3 weeks
Topics: End-to-end project using real datasets
Hands-on: Apply R skills to analyze, model, and visualize data
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Job Outlook
R is in high demand for roles such as Data Analyst, Statistician, and Research Scientist.
Ideal for candidates entering roles in academia, healthcare, finance, and policy research.
Median salary ranges from $65K–$115K depending on role and experience.
R remains a top skill for statistical analysis and data visualization tasks.
Specification: Applied Data Science with R Specialization
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