Data Science with R
An introduction to the R programming language, focusing on the fundamental data structures, control flow, and functional programming concepts needed for data analysis. It also covers essential utilities for importing data, debugging code, and running statistical simulations.
What This Course Covers
Data Science with R is structured into 10 chapters that build on each other progressively:
Each chapter combines interactive AI tutoring with hands-on examples. After you learn the material, Lambdio's spaced repetition algorithm schedules review sessions at optimal intervals — so you retain concepts and techniques long-term.
How to Study Data Science with R on Lambdio
Lambdio's AI-powered platform adapts to how Computer Science courses are best learned. Here's our recommended approach:
Data Science with R is a code-heavy introductory course that teaches programming fundamentals alongside data analysis. Standard Mode is the ideal learning mode because mastering R syntax, vectorized operations, dplyr verbs, and the apply family requires structured explanations, live code demonstrations, and hands-on practice — all of which Standard Mode delivers through interactive tutorials with comprehension checks. Socratic Mode would be less effective here since discovering R's subsetting rules or scoping behavior through Socratic questioning alone would be slow without direct code exposure. The Easy difficulty of this course makes Low priority the appropriate default — the material is foundational and accessible, so a less frequent review schedule is sufficient. For quick terminology checks on data types, dplyr verbs, and function syntax, use Quiz Mode to reinforce the basics before progressing to more advanced data analysis courses.
Interactive Quiz
Test your knowledge with these sample questions from the course. Tap an answer to see if you're right:
<- do in R?[ and [[?read.table() can double execution speed by pre-specifying column types?next command do inside an R loop?sapply() function return when every element of the result has length 1?What You'll Be Able to Do After This Course
- ✓Write and execute R code using variables, atomic data types, vectors, lists, matrices, and data frames
- ✓Subset and index R objects using bracket operators, logical conditions, and element-wise operations
- ✓Import tabular data from CSV files and text connections, and optimize loading for large datasets
- ✓Implement conditional logic and iteration using if-else statements, for loops, and while loops
- ✓Define custom R functions, apply lexical scoping rules, and leverage lazy evaluation and argument matching
- ✓Use the apply family of functions (lapply, sapply, apply, mapply, tapply) for concise functional looping
- ✓Manipulate and transform data frames using dplyr verbs and the pipe operator for readable workflows
- ✓Debug R code using traceback, debug, browser, trace, and recover, and profile performance with system.time
Frequently Asked Questions
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