Data science courses with R in Frankfurt!
R is one of the leading programming languages for data analysis. In our R trainings, we teach you the manifold possibilities of the free programming language in a practically orientated and comprehensive way. Unlock the potential of data science with the free R programming language for advanced analytics and data visualization. With over 1,500 satisfied participants, eoda’s R courses are among the leading courses in the German-speaking world.
This time we bring our popular courses „Introduction to R“ and „Introduction to Machine Learning with R“ to Frankfurt.
12th – 13th November 2019 | Introduction to R
With practical tips and exercises, this introductory course serves as a basis for the further use of R in individual applications. In order to be able to lay the foundation for independent work, the focus lies on teaching the logic and terminology of R. This course is aimed at beginners and therefore does not require any previous in-depth knowledge.
14th – 15th November 2019 | Machine Learning with R
In this course you will gain an insight into machine learning algorithms. In addition to developing your own models, you will also learn what challenges you face and how to master them with R. Use machine learning and data mining algorithms to develop artificial intelligence applications based on data.
By means of practical examples and exercises, this course teaches you the skills to carry out machine learning procedures in R independently.
These two introductory courses can also be booked as a bundle at an attractive price.
Save one of the coveted places and become a data science expert in November with R! We look forward to your registration. Read more.
Vanessa Roy - Beitrag vom 27.08.2019
Vanessa Roy studiert English and American Culture and Business Studies an der Universität Kassel und unterstützt das Marketing bei der eoda GmbH. Neben den abwechslungsreichen Tätigkeiten in diesem Bereich, schätzt sie ebenfalls die tiefgründigen Einblicke in die facettenreichen Entwicklungen im Rahmen von Data Science.