Public administration

R - introductory course

Level: beginners

Workload: 2x8h (2 days)

  1. Introduction to R – overview of the RStudio interface and key functionalities
  2. Data formats and variable types
  3. Indexing techniques for efficient data handling
  4. Data manipulation and preparation – fundamentals of dplyr
  5. Automating repetitive tasks with loops
  6. Writing and utilizing functions in R
  7. Fundamentals of data visualization
  8. Streamlining workflows with dplyr and ggplot2 – pipeline processing
  9. Integrating AI (ChatGPT) in coding – practical applications, benefits, and limitations

Data visualisation - basics

Level: beginners

Workload: 2x8h (2 days)

  1. Importing data from various formats (TXT, CSV, XLSX)
  2. Data preparation for analysis using tidyr, dplyr, stringr, and forcats
  3. Fundamentals of effective data visualization
  4. Principles of research presentation – tailoring the format for clarity and impact
  5. Introduction to ggplot2 – the Grammar of Graphics
  6. Practical application of ggplot2 – hands-on project with expert guidance
  7. Leveraging AI (ChatGPT) in coding – use cases, benefits, and potential challenges

Data visualisation - advanced

Level: advanced

Workload: 2x8h (2 days)

  1. Principles of effective research result visualization
  2. Advanced data presentation techniques using dplyr and ggplot2
  3. Visualization methods tailored to variable scales:
    • Nominal scale
    • Ordinal scale
    • Interval and ratio scale
    • Combining variables from different scales
  4. Correlation analysis and data relationships
  5. Heatmaps for pattern recognition and trend analysis
  6. Introduction to mapping techniques
  7. Leveraging AI (ChatGPT) in coding – applications, benefits, and challenges

Statistics with R

Level: beginner

Workload: 2x8h (2 days)

  1. Data preparation techniques
  2. Fundamentals of descriptive statistics
  3. Data manipulation and pipeline processing with dplyr
  4. Key topics in statistics and statistical inference using R:
    • Group characteristics analysis
    • Univariate data analysis
    • Correlation and regression analysis
    • Time series analysis
  5. Effective result visualization with ggplot2
  6. Utilizing AI (ChatGPT) in coding – applications, benefits, and potential challenges
  7.  

Reporting automatisation in R

Workload:  3x8h (3 days) 

Introduction to R and Data Processing

  1. Getting Started with R
    • Installing and configuring R and RStudio
    • Fundamentals of R syntax: variables, operators, and functions
    • Working with packages: tidyverse, data.table, openxlsx
  2. Data Processing and Analysis
    • Importing data from various sources (Excel, CSV, TXT, SQL)
    • Data cleaning and transformation using dplyr and tidyr
    • Basic statistical analysis and data aggregation
  3. Automating Data Processing
    • Streamlining workflows and automating repetitive tasks

Visualization and Automated Reporting

  1. Data Visualization
    • Creating visualizations with ggplot2
    • Introduction to thematic mapping for administrative data
    • Developing interactive dashboards using R Shiny
  2. Automated Reporting
    • Generating reports in R Markdown (PDF, Word, HTML)
  3. Practical Application
    • Hands-on project with expert guidance
  4. Leveraging AI in Coding
    Using AI (ChatGPT) in coding – applications, benefits, and limitations
Sleek laptop showcasing data analytics and graphs on the screen in a bright room.

R on-demand

Workload:  depending on the course scope

Customize Your Course to Fit Your Needs

Design a course tailored to your specific requirements by selecting from our standard offerings or incorporating advanced topics beyond the core curriculum. Examples include modeling extreme phenomena using theoretical distributions or automating reporting processes.

The possibilities are virtually limitless.

Where devil can’t go, R rises to the challenge.

For complex cases, we welcome the opportunity to demonstrate our expertise.