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DTSTAMP:20260407T181343Z
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DTSTART:20260615T090000Z
DTEND:20260619T170000Z
DESCRIPTION:This course will introduce life scientists to practical data sc
 ience methods increasingly used in research\, with a particular focus on s
 tatistics and machine learning\, using Python as the language of choice. P
 articipants will learn how to prepare\, process\, and visualise some key b
 iological datatypes\, and gain hands-on experience in training and evaluat
 ing machine learning models using publicly available data.   \n  \nThe co
 urse will combine morning lectures (supported by short practical exercises
  where relevant) with afternoons working on group projects\, providing ind
 ependent\, hands-on experience in applying what is learnt to research ques
 tions. Trainers and mentors will be available throughout to guide particip
 ants and offer advice and feedback.  \n \n\n**Group projects**\n\nA centr
 al part of the course is the group project. You will work in small groups\
 , applying machine learning approaches to a biological question of interes
 t. These projects will follow a framework suggested by the mentors\, but b
 e driven by participants\, with as much support and input from mentors as 
 you need.  \n  \nDuring the application process\, you will be asked to ind
 icate your preferences from a list of possible biological applications and
 /or data types for the group project work\, including\, among others\, gen
 e expression\, structural biology\, and bioimaging. During the course\, fo
 llowing a framework provided by project mentors\, each group will finalise
  their project aims\, collect and process data\, and apply machine learnin
 g approaches to address their research question. Groups will receive regul
 ar feedback and support from mentors\, and are expected to take an active 
 role in driving their projects forward collaboratively.\n\nThere will be d
 aily opportunities to present progress so far and receive feedback\, and t
 he projects will end with a flash-talk session on the last day\, giving pa
 rticipants the opportunity to present the data\, methods\, and insights th
 ey have developed during the training.
LOCATION:European Bioinformatics Institute\, Hinxton
SUMMARY:Data science for life scientists
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/data-science-for-life-s
 cientists-2026
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