Course Description

The aim is to teach participants of the workshop basics of data analysis and visualization. We are up to provide a hands-on experience in these fields using real-life data set and R programming language. Thus, everyone is encouraged to use their own laptops during the workshop, with R and RStudio installed beforehand.

Course topics

  1. Getting Started with R and RStudio
  2. Introduction to R
  3. Starting with data
  4. Data management with R data.frame
  5. Data management with dplyr

Course tools

R, RStudio


Although we will review some of the features of R programming language, you do not need to know R beforehand.

What should I do before the workshop? Install R and RStudio:


Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. During the workshop run RStudio using Run as administrator (mouse right click on the RStudio icon and choose “Run as administrator” ) option to avoid issues related to limited user rights.

Mac OS X

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.


You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). This workshop requires a version of R no older than version 3.2.2; the default software repositories for some Linux distributions may be out of date. It is recommended that you use a more recent version of R by adding the relevant entries to your package manager. See the instructions for your distribution on the CRAN website. Also, please install the RStudio IDE.

Please, pay attention! If you already have R installed, make sure that its version is not older than 3.2.2 (how do I check version of R?).

Few links to check out (optional):

If you are curious about R programming language, you can check the links below before the workshop:


Mr. Dmytro Fishman
Junior Researcher, PhD candidate at the University of Tartu

Dmytro is a Junior Researcher and a PhD candidate at the University of Tartu. His current research is focused on applying machine learning and data mining methods to biological data. For his PhD thesis, Dmytro is building an automatic tool for analysing protein microarray experiments in immunological studies. He and his colleagues use Deep Learning on various biological data, including genomic data and microscopy images. Also Dmytro has experience teaching various machine learning related subjects both at the University of Tartu and as an invited lecturer in companies. He is a certified trainer in Data Carpentry and Software Carpentry organisations that organise and carry out trainings for scientists in the core data science skills around the world.

Fields of interests: Data Mining, Machine Learning, Bioinformatics, Image Recognition, Deep Learning, Advanced Algorithms.