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VERSION:2.0
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CALSCALE:GREGORIAN
BEGIN:VEVENT
DTSTAMP:20260704T072809Z
UID:3a8fdd2d-5a29-4358-9d8d-1c7470589750
DTSTART:20191209T093000Z
DTEND:20191213T170000Z
DESCRIPTION:THIS EVENT IS NOW FULLY BOOKED!\n\nThe aim of this 5 days cours
 e is to develop motivated participants toward becoming independent BioImag
 e Analysts in an imaging facility or research role. Participants will be t
 aught theory and algorithms relating to bioimage analysis using Python as 
 the primary coding language.\n\nLectures will focus on image analysis theo
 ry and applications. Topics to be covered include: Image Analysis and imag
 e processing\, Python and Jupyter notebooks\, Visualisation\, Fiji to Pyth
 on\, Segmentation\, Omero and Python\, Image Registration\, Colocalisation
 \, Time-series analysis\, Tracking\, Machine Learning\, and Applied Machin
 e Learning. \n\nThe bulk of the practical work will focus on Python and ho
 w to code algorithms and handle data using Python. Fiji will be used as a 
 tool to facilitate image analysis. Omero will be described and used for so
 me interactive coding challenges. \n\nResearch spotlight talks will demons
 trate research of instructors/scientists using taught techniques in the wi
 ld. \n\nThis event is organized in collaboration with the [Image Analysis 
 Focused Interest Group](http://iafig-rms.org/) and is sponsored by the [Ro
 yal Microscopical Society](https://www.rms.org.uk/).\n\nThe training room 
 is located on the first floor and there is currently no wheelchair or leve
 l access available to this level.\n\nPlease note that if you are not eligi
 ble for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/fa
 q/raven/n5) account you will need to book or register your interest by lin
 king [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=31
 29158&amp\;course-title=BioImage%20analysis%20with%20Python).''
LOCATION:Craik-Marshall Building
SUMMARY:IAFIG-RMS: Bioimage analysis with Python
URL;VALUE=URI:http://training.csx.cam.ac.uk/bioinformatics/event/3129158
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