Introduction to the basics of R and its data structures. Case study with movie data to showcase data cleaning and manipulation. Case study with marketing data to experiment with machine learning techniques.

Introduction to the basics of R and Python, and their data structures. Highlight similarities and differences. Short overview of the data analysis process, so you can start your own analyses in R or Python.

An introduction to the basics of R, such as vectors, list and data frames. Case study on geographical data to plot unemployment in Germany's states, and case study on bank data in a marketing context.

Case study with library data, going through the entire process of data analysis. Deeper dive into building business dashboards by combining knitr with automated jobs.

Emergent's first R workshop focussed on the basics of R, such as data structure, descriptive statistics and simple plots. In this follow-up workshop, organized by DataCamp, we'll take things one step further. In a case study format, we'll go through the typical data analysis process, going from importing data to cleaning data over building models, to finally visualizing and reporting your findings.

An introduction to the basics of R, such as vectors, lists and data frames. After hands-on practice in the DataCamp interface, some real-life case studies are discussed to demonstrate the entire data analysis process.

A crash course into the R language. Hands-on case study where decision trees are used to better target marketing efforts in a banking context.

A crash course into the R language. Hands-on case study where data from the Open Movie Databases is imported, cleaned, modelled, visualized and finally reported.