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R for Data ScienceUusi
A comprehensive beginner-to-advanced track that takes learners from foundational R programming and data wrangling to professional visualization, predictive modeling, and automated reporting workflows using R.
R IntroductionUusi
Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.
Introduction to Jupyter notebook: RUusi
This project settled for beginners to learn the very basic principles and concepts of Jupyter notebooks with R.
Maximize the Expression
Find the maximum value of an expression formed by three integers using + and * operations.
R BasicsUusi
A beginner-level quiz covering fundamental concepts of the R programming language, including assignment, data types, vector operations, functions, and basic syntax. Questions include code interpretation, function identification, and output prediction.
Data Visualization with R Uusi
A beginner-friendly track designed to introduce learners to the fundamentals of data visualization using R. Starting from the basics of R programming, learners will build skills in preparing data, creating essential visualizations with ggplot2, and applying best practices for visual storytelling. The track culminates in a practical project where students create a complete data visualization report using real-world data.
R Introduction: Part IIUusi
In the second part of R Introduction, you will learn about multi-dimensional built-in structures, such as matrices, data frames, and lists.
One Flip Game
Maximize the number of ones in a binary array after one flip operation.
R Advanced ConceptsUusi
This quiz assesses advanced knowledge of R programming, focusing on data structures, evaluation strategies, functional programming, and key differences between similar functions and operators. Questions include code output prediction, conceptual differences, and practical applications of advanced R features.
Data Analyst with RUusi
A beginner-friendly, step-by-step learning track designed to equip aspiring data analysts and junior professionals with the essential skills to analyze data using R. This track covers foundational programming, data structures, cleaning and wrangling, exploratory data analysis, and data visualization, ensuring learners are job-ready for entry-level data analyst roles.
Visualization and Reporting with RUusi
Master the essentials of data visualization and reporting in R. Learn to create compelling graphics, perform exploratory data analysis, and communicate insights effectively using R's powerful tools.
Cake Division
Determine if a cake can be split into two even-weight portions.