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DTSTAMP:20260616T153956Z
UID:af0b9fe2-3155-41b4-8c8b-c5850ce4d937
DTSTART:20191016T090000Z
DTEND:20191018T170000Z
DESCRIPTION:Educators:\nMalvika Sharan\, Georg Zeller\, Mike Smith\, Thomas
  Schwarzl\, Frank Thommen (HD-HuB)\, Holger Dinkel\n\nDate:\n16-10-2019 - 
 18-10-2019\n09:00-18:00\n\nLocation:\nATC Computer Training Lab\, EMBL Hei
 delberg\n\nContents:\nComputation is an integral part of today's research 
 as data has grown too large or too complex to be analysed by hand. An ever
 -growing fraction of science is performed computationally and many wet-lab
  biologists spend part of their time on the computer. Many scientists stru
 ggle with this aspect of research as they have not been properly trained i
 n the necessary set of skills. The result is that too much time is spent u
 sing inefficient tools when progress could be faster. This course provides
  training in several key tools\, with a focus on good development practice
 s that encourage efficient and reproducible research computing.\n\nTopics 
 covered include:\n\n    Introduction to Python scripting\n    Introduction
  to the Unix shell and usage of cluster resources\n    Version control wit
 h Git and Github\n    Analysis pipeline management\n    Scientific Python 
 &amp\; working with biological data\n    Literate programming with Jupyter
  notebooks\n\nLearning goals:\nThis course aims to teach software writing 
 skills and best practices to researchers in biology who wish to analyse da
 ta\, and to introduce a toolset that can help them in their work. The goal
  is to enable them to be more productive and to make their science better 
 and more reproducible.\n\nPrerequisites:\nThis is a course for researchers
  in the life sciences who are using computers for their analyses\, even if
  not full time. The target student will be familiar with some command line
 /programmatic computer usage\, will want to become more confident using th
 ese tools efficiently and reproducibly. A target student will have written
  a for loop in some language before\, but will not know what git is (or at
  least not be very comfortable using git).\n\nKeywords:\nProgramming\; Com
 mand Line\; Version Control\; Bioinformatics\; Data Analysis\; Cluster Com
 puting\n\nTools:\nPython\; Bash\; Unix/Linux\; Git\; GitHub\; SnakeMake\; 
 Biopython\; Pandas\; Numpy\; SciPy\; Matplotlib\n
LOCATION:Heidelberg
SUMMARY:Software Carpentry Workshop
URL;VALUE=URI:https://www.denbi.de/training/486-software-carpentry-workshop
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