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Course Outline

Introduction to R Markdown

  • Overview of R Markdown and its benefits
  • Installation and configuration within RStudio
  • Understanding the basic structure of R Markdown documents

Managing Code Chunks

  • Creating and customizing code chunks
  • Controlling output display and chunk behavior
  • Integrating plots, tables, and inline R code

Text Formatting and Markdown Syntax

  • Applying headings, lists, links, and emphasis
  • Incorporating tables and images
  • Using LaTeX for mathematical notation

Output Formats and Rendering

  • Rendering documents to HTML, PDF, and Word
  • Utilizing YAML headers to manage output parameters
  • Navigating the knit process and resolving common errors

Advanced Document Capabilities

  • Implementing parameterized reports
  • Building conditional content and interactive documents
  • Reusing content via child documents

Customization and Styling

  • Applying themes and templates
  • Defining custom styles using CSS and LaTeX
  • Adding title pages, table of contents, and cross-references

Publishing and Collaboration

  • Sharing R Markdown projects via Rpubs, GitHub, or corporate websites
  • Collaborative workflows and version control strategies
  • Best practices for ensuring reproducible reporting

Conclusion and Future Directions

Requirements

  • Foundational knowledge of R syntax and core functions
  • Experience with the RStudio environment
  • General understanding of data analysis processes

Target Audience

  • Data analysts and data scientists
  • Researchers and academic professionals
  • Report writers and documentation specialists working with R
 14 Hours

Number of participants


Price per participant

Open Training Courses require 5+ participants.

Testimonials (3)

a multitude of points

Joanna - Instytut Ekonomiki Rolnictwa i Gospodarki Zywnosciowej-PIB
Course - Statistical Analysis with Stata and R

knowledge of the trainer, tailor based, all topics covered

eleni - EUAA
Course - Forecasting with R

The real life applications using Statcan and CER as examples.

Matthew - Natural Resources Canada
Course - Data Analytics With R

Upcoming Courses

R Markdown for Dynamic Documents and Reproducible Reporting

2026-10-07 09:30
14 hours
Rome
2100 EUR (Online)
2500 EUR (Classroom)

R Markdown for Dynamic Documents and Reproducible Reporting

2026-10-21 09:30
14 hours
Milan
2100 EUR (Online)
2500 EUR (Classroom)

R Markdown for Dynamic Documents and Reproducible Reporting

2026-11-04 09:30
14 hours
Naples
2100 EUR (Online)
2500 EUR (Classroom)

R Markdown for Dynamic Documents and Reproducible Reporting

2026-11-18 09:30
14 hours
Turin
2100 EUR (Online)
2500 EUR (Classroom)

R Markdown for Dynamic Documents and Reproducible Reporting

2026-12-02 09:30
14 hours
Genoa
2100 EUR (Online)
2500 EUR (Classroom)

R Markdown for Dynamic Documents and Reproducible Reporting

2026-12-16 09:30
14 hours
Bologna
2100 EUR (Online)
2500 EUR (Classroom)

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