W1
Beginner
3 sessions · 6 hrs
Week 1: R Fundamentals and Environment Setup
RStudio, vectors, data types, operators, control flow, functions, packages
A complete 12-week R curriculum from fundamentals and the tidyverse through statistical inference, machine learning, and a capstone project. Each week ships with a runnable R script for RStudio, theory, and graded assignments. Built by Adeleke Akinrinade Kayode for professionals entering the UK and Nigerian data science job markets.
RStudio, vectors, data types, operators, control flow, functions, packages
Vectors, matrices, data frames, lists, advanced indexing and operations
dplyr's 5 verbs, tidyr, the pipe operator, professional workflows
Missing values, duplicates, type fixes, standardisation, outliers
Statistical summaries, distributions, the ggplot2 visualisation masterclass
Distributions, sampling, Central Limit Theorem, confidence intervals
t-tests, ANOVA, chi-square, non-parametric tests, effect sizes
Simple and multiple linear regression, logistic regression, diagnostics
Decision trees, random forests, model evaluation and tuning in R
K-means, hierarchical clustering, PCA and dimensionality reduction
Trends, seasonality, decomposition, forecasting and ARIMA in R
End-to-end R project, reproducible research, professional reporting
R quick-reference cheat sheet and the package installation / environment setup guide.