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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.

Data Analysis with R

Gain practical experience in data analysis with R by learning how to clean, transform, and visualize datasets. Explore essential workflows such as selecting and filtering data, handling missing values, and summarizing results. Build confidence in preparing data for insights, reporting, and deeper statistical exploration.

Control Flow in R

Master the essentials of control flow in R, including conditional statements, loops, and the powerful apply family of functions. This course is designed for beginners and will guide you through practical, real-world examples to help you write efficient and readable R code.

Data Manipulation in R

Master the essential data manipulation skills in R using dplyr, grouping and aggregation, and joining data frames. This course is designed for beginners and provides hands-on, real-world tasks to build your confidence in transforming and analyzing data for analytics.

Functions and Functional Programming in R

Master the art of writing and using functions in R, from basic syntax to advanced functional programming techniques. This course guides you through creating your own functions, leveraging anonymous functions, and applying functional programming concepts to solve real-world problems in R.

R for Data Scientists

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 Economists

Learn how economists use R to analyze macroeconomic and market data, build econometric models, and interpret results for policy and market decisions. Focus on regression, time series, and forecasting using real economic datasets.

R for Financial Analysts

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.

R for Marketing Analysts

Learn to apply R for practical marketing analytics: measure KPIs, analyze customers and cohorts, evaluate campaigns, and visualize insights to drive business decisions.

R for Mathematicians

Master mathematical computation in R: express vectors, matrices, and mathematical structures in code, apply numerical methods, and solve equations and optimization problems with mathematical rigor.

R for Statisticians

Master rigorous statistical analysis in R: probability, inference, ANOVA, regression, simulation, and interpretation. Emphasizes statistical reasoning, uncertainty, and correct conclusions using R as a computational tool.

Visualization and Reporting with R

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.

Working with Data Structures in R

Master the essential data structures in R, including lists, data frames, and factors. Learn how to create, manipulate, and analyze data using R's powerful tools, with engaging explanations and real-world challenges designed for beginners.

Working with Text, Dates, and Data Cleaning in R

Master the essentials of handling text, dates, and files in R. This course guides you through string manipulation, regular expressions, date-time operations, and file I/O, with engaging explanations and practical challenges for beginners.

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