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DTSTAMP:20260309T174951Z
UID:f49d5054-1d43-4e93-a7ec-003db3eb0ebc
DTSTART:20240122T080000Z
DTEND:20240129T160000Z
DESCRIPTION:Educators:\nRenato Alves\, Lisanna Paladin\, Christian Schudoma
  (HD-HuB) Fotis Psomopoulos (ELIXIR-GR)\,  \n\nDate:\n22/01/2024 - 26/01/2
 024\n\nLocation:\nEMBL Heidelberg and Virtual (Hybrid)\n\nContents:\nThe m
 issing step between data collection and research progress is a lack of tra
 ining for researchers in crucial skills for effectively managing and analy
 sing large amounts of data. This hands on workshop teaches researchers the
  fundamental data skills they need to conduct their work\, and provides hi
 gh-quality\, domain-specific training covering the full lifecycle of data-
 driven research. The domain-specific approach allows participants to tailo
 r the data\, content\, and tools to reflect the specific data and analysis
  needs of different areas:\n- Data organisation and cleaning\n- Versioning
  with Git\n- Introduction to R\n- Data analysis and visualisation in R\n- 
 Data analysis with applications to genomics\n\n Learning goals:\nYou will 
 learn...\n- how to organise data and some practices for more effective dat
 a handling\n- to effectively clean and format data and automatically track
  any changes\n- to use R to handle\, filter\, and summarise tabular data\n
 - to use the split-apply-combine concept for data analysis\n- to visualise
  the results of these analyses in R using the ggplot2 library\n- to apply 
 all of the concepts in an exploratory analysis of a typical biological dat
 aset\n\nPrerequisities:\nThe course is aimed at graduate students and othe
 r researchers in the life sciences who would like to learn good practices 
 in data management and analysis. The course is ideally suited to students 
 without prior experience in computational research\, but some familiarity 
 with working with tabular data on a computer is welcome.\n\nKeywords:\nDat
 a Carpentry\, R\n\nTools:\nR
LOCATION:EMBL Heidelberg\, 1 Meyerhofstraße
SUMMARY:Data Carpentry 2024
URL;VALUE=URI:https://www.denbi.de/training-courses-2024/1688-data-carpentr
 y-workshop-2024
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