Introduction to R for Data Science


29.03. - 01.04.2022


09:00 - 12:30 Uhr

Workshop für Promovierende und Postdocs der Universität Bremen


Referent*in:
Lukas Löber (eoda)

Ort:
Online

Anmeldung:
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COURSE DESCRIPTION
The open source language R is one of the best solutions for data analysis, data visualization, data mining and predictive analytics. With R, a unique standard of functionality, quality and actuality can be achieved. The course deals with the following topics:

  • First steps into R
  • Concept and philosophy of R
  • Data structures and their properties
  • Importing data
  • Data management
  • Data analysis with R
  • For loops and control elements
  • Visualizations with R
  • Introduction to the leading IDE RStudio

OBJECTIVES
The objective of the course is to teach the participants the logic and terminology of R and to lay the foundation for working with R independently.

TARGET AUDIENCE
The course is intended as an introduction to R and its basic functionalities. It makes it easier for participants to get started with R by getting practical tips and exercises. This basic course serves R beginners without previous knowledge as a starting point in order to use R in further individual application scenarios. For R beginners, this course set an ideal foundation to participate in our advanced R courses Machine Learning in R an Time Series Analysis with R.


ABOUT THE TRAINER
Lukas Löber is a data scientist at eoda GmbH with a background in economics. His daily work includes working on cross-sectoral data science projects and teaching R.

eoda GmbH is an IT company specialized in Data Science working towards the mission “Data Science Empowerment”. As a pioneer in Germany for open-source programming languages and as a Full Service Certified Partner of RStudio and Anaconda, eoda offers a holistic training and qualification concept – with a performant toolset around programming languages like R, Python and Spark.
The interdisciplinary team of eoda combines deep knowledge of business processes with the competent application of the appropriate analytic methods and can draw from experiences in cross-disciplinary use cases. Learn more about eoda .