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Udforsk forløb, kurser og projekter – alt på ét sted. Lær i dit eget tempo, og opbyg færdigheder fra den virkelige verden.
R for Data Science
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 Introduction
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.
Maximize the Expression
Find the maximum value of an expression formed by three integers using + and * operations.
R Advanced Concepts
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 Visualization with R Ny
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.
Visualization and Reporting with RNy
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.
One Flip Game
Maximize the number of ones in a binary array after one flip operation.
Data Analyst with RNy
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.
R for Financial AnalystsNy
Learn to analyze financial data in R: work with time series, compute returns, assess risk, analyze portfolios, and visualize and forecast market data using practical, code-driven examples.
Cake Division
Determine if a cake can be split into two even-weight portions.
R for Data ScientistsNy
Master practical data science in R by learning data cleaning, modeling, evaluation, and machine learning workflows through hands-on code. Build fluency with R syntax, functions, and outputs for real-world data science tasks.
R for Marketing AnalystsNy
Learn to apply R for practical marketing analytics: measure KPIs, analyze customers and cohorts, evaluate campaigns, and visualize insights to drive business decisions.
