Venue: Room C0106
Instructors: Like Fokkens (UvA), Saskia Hiltemann (Erasmus MC), Mattias de Hollander (NIOO-KNAW), Marc Galland (UvA)
Helpers: Fleur Gawehns (NIOO-KNAW), Raúl Wijfjes (WUR), Vittorio Tracanna (WUR), Miaomiao Zhou (Avans), Thijmen Breeschoten (WUR)
More information: course website

Target group:
The course is aimed at graduate students and other researchers. You don’t need to have any previous knowledge of the tools that will be presented at the workshop.

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience.
The focus of this workshop will be on working with genomics data and data management and analysis for genomics research. We will cover project setup, connecting to and using cloud computing, the command line for sequence quality control and bioinformatics workflows. We will not be teaching any particular bioinformatics tools, but the foundational skills that will allow you to conduct any analysis and analyze the output of a genomics pipeline.
Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.
Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.

Requirements:
Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (please see the course website). They are also required to abide by Data Carpentry’s Code of Conduct.

Sponsors & Supporters:
This workshop is sponsored and supported by ELIXIR-EXCELERATE, NIOO-KNAW, UvA and the Graduate School Experimental Plant Sciences. ELIXIR-EXCELERATE is funded by the European Commission within the Research Infrastructures programme of Horizon 2020, grant agreement number 676559.