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Master in R for Data Science and Machine Learning

Master in R for Data Science and Machine Learning


Master in R for Data Science and Machine Learning Learn to program in R, the language for Data Science, Machine Learning and data visualization. Learn R from scratch

What you'll learn

  • Aprenderás a programar en R mediante la herramienta RStudio
  • Aprenderás a crear visualizaciones de datos con R y RStudio
  • Aprenderás R para Data Science
  • Aprenderás R para análisis de datos
  • Aprenderás a usar los algoritmos de Machine Learning con R
  • Aprenderás a manejar la herramienta RStudio
  • Aprenderás redes neuronales para Machine Learning con R
  • Aprenderás a cargar datasets o conjuntos de datos en RStudio
  • Aprenderás a crear impresionantes gráficos interactivos con R y RStudio


Data Science and Machine Learning professionals are currently the highest paid technical profiles.

This master is designed to learn from scratch, step by step, until you become an expert.

Everything is explained by examples to facilitate learning

These are the topics covered in this master:

  • Environment setup (R and RStudio installation)
  • Introduction to R (arithmetic operations, variables, data types, vectors, comparison operators, help and documentation)
  • Matrices in R (arithmetic operations with matrices, selection of elements, selection by rows and columns, factor function)
  • Data Frames in R (creation of Data Frames, dataset, selection and ordering, exporting and importing data, handling null values)
  • Lists in R (creation and management of lists)
  • Data input and output in R (csv files, excel files, databases)
  • Basic R programming (logical operators, if else conditionals, while loop, for loop, functions)
  • Advanced R programming (predefined functions, functions on vectors, anonymous functions, mathematical functions, regular expressions, dates and times)
  • Data manipulation with R (data manipulation with dplyr, pipe operator, data cleaning with tidyr)
  • Data visualization with R (histograms, scatterplots, barplots, boxplots, distribution graphs, limits and dimensions)
  • Interactive charts with Plotly
  • Introduction to Machine Learning
  • Machine Learning - Linear Regression in R
  • Machine Learning - Logistic Regression in R
  • Machine Learning - K Nearest Neighbors in R
  • Machine Learning - Decision Trees in R
  • Machine Learning - Random Forest in R
  • Machine Learning - Support Vector Machines in R
  • Machine Learning - K means in R
  • Deep Learning - Neural Networks in R

Join this course and become a data scientist!

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