Oct 8 - 9, 2016
9:00 am - 5:00 pm
Instructors: Nasťa Zidkova, Filip Sedlák, Petr Šimeček, Libor Mořkovský
Helpers: Václav Gergelits, Vojtěch Filipec, Petr Švarný, Michal Kahle
This course will help you to use the computer more efficiently during your research. We'll show you how to automate repetitive procedures like manipulating files, computing statistics and creating charts from your data. This will help you make your analyses less error prone and reproducible.
If you're eager to learn but you don't see the use of such skills in your research, don't worry. The more you know, the more cases you'll see where you can apply your newly acquired skills.
Who: 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.
Where: Vídeňská 1083, Prague. Get directions with Mapy.cz
Requirements: Participants must bring a laptop with a few specific software packages installed (listed below).
Price: This course is offered to you at courtesy of the instructors and helpers. Please smile at them. :-) There is no budget for food and beverages. If you'd like to return the favour, you're more than welcome to bring in any meal or snack.
Contact: Please mail firstname.lastname@example.org for more information.
Registration is closed now :-( See you next time!
Don't take the schedule too seriously, it may change.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.
Basic Software Carpentry course teaching R programming.
R course focused on manipulating data.
Course from Data Carpentry teaching how to analyze genomics data using R and commandline tools.
To participate in a Software for Scientists workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
R Studio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.
RStudio makes R easier to use. We'll teach the course using R Studio.