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R Foundation

Learn how to use the R programming language effectively

Requirements:
  • No experience required

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Who is the course for

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In this course, you will learn how to effectively use this flexible tool not only for statistical data analysis, but also for data science, machine learning, data visualization and reporting. Take your company's decision-making to the next level with the knowledge and skills from the R course.

Target audience

  • Data Scientists

  • Data analysts

  • Qualitative professionals

  • Anyone who wants to learn how to program

What will you learn

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  • You will learn how to manipulate, clean and prepare data for analysis.
  • You will master the creation of dynamic reports that save time and increase efficiency.
  • You will learn methods for data processing and application of machine learning algorithms.
  • You will learn how to present data and results through clear and compelling visualizations.
  • You will learn how to apply the skills you have learned to specific challenges in practice, thereby improving your decision-making skills.

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This course can be customized - either as an individual training 1:1 or for your team. Just leave us your contact and we will contact you with options tailored to your needs.

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Timeline

1st Day

09:00 – 10:30 Getting to know R
  • Introduction to the world of R
  • Installing R, user interface, help, command history, workspace, scripting, packages.
  • R as an advanced calculator
10:30 – 10:45 Coffee break
10:45 – 12:15 Data types and structures
  • Variables and functions in R, vectors, matrices and arrays, related operations and functions
12:15 – 13:45 Lunch
13:45 – 15:15 Data types and structures
  • Sheets and data frame, related operations and functions
15:15 – 15:30 Coffee break
15:30 – 17:00 Data structures, Programming basics
  • Factors and tables, related operations, functions and additional packages
  • Programming basics: if condition , for loop, while loop and repeat loop. Using vector operations instead of loops.

2nd Day

09:00 – 10:30 Repetition and practice
  • Interesting examples
10:30 – 10:45 Coffee break
10:45 – 12:15 Function
  • Creating user functions and programming with functions
12:15 – 13:45 Lunch
13:45 – 15:15 Basic graphic visualization in R
  • Graphics basics in R: basic graphics and its capabilities
15:15 – 15:30 Coffee break
15:30 – 17:00 More advanced graphical visualization using ggplot2
  • Visualisation with the ggplot2 package

3rd Day

09:00 – 10:30 Working with text
  • Text processing in R: input from file and keyboard, output to file and screen, working with text, regular expressions.
10:30 – 10:45 Coffee break
10:45 – 12:15 The world of the tidyverse
  • The tidyverse package system (dplyr , tidyr etc.)
12:15 – 13:45 Lunch
13:45 – 15:15 Rmarkdown
  • A tool for combining text, code and analysis results into a single document that can be easily exported to different formats.
15:15 – 15:30 Coffee break
15:30 – 17:00 Final project
  • Practice of the discussed content on dataset
  • Block length 90 min.
  • Teaching hours 24
  • Refreshments Yes
  • Exam No

The course covers working with R and RStudio for effective data manipulation, statistical analysis, machine learning, visualization and report automation, giving individuals the skills for career growth and giving organizations a competitive advantage through better decision making and innovation.

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before you come to the course

Contains consolidated terms and definitions of thousands of managerial terms in the field of project, program, portfolio, risk, enterprise architecture, security and personal data protection.

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Your next career step

Data analysis in R

Data analysis in R

Improve in quantitative analysis with emphasis on the use of appropriate methods.

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