BEGIN:VCALENDAR VERSION:2.0 PRODID:www.eu-parc.eu BEGIN:VEVENT UID:6aab5d2260f70 DTSTART;VALUE=DATE:20261001 SEQUENCE:0 TRANSP:OPAQUE DTEND;VALUE=DATE:20261002 SUMMARY:Introduction to Machine Learning with Python CLASS:PUBLIC DESCRIPTION:The Introduction to Machine Learning with Python course\, organ ised by SIB\, will take place on 1-2 October 2026 at the University of Ber n\, Switzerland. This two-day course will introduce participants to common machine learning (ML) methods and their application to omics data in biol ogy and medicine. Through extensive hands-on exercises using Python and th e scikit-learn ML framework\, participants will explore the main categorie s of machine learning\, learn how to select and implement appropriate algo rithms\, and critically evaluate their use in omics studies. The course wi ll also develop practical skills in interpreting and visualising the resul ts of ML analyses using real-world biological and medical datasets.Target audienceThis course is particularly relevant for PhD students\, postdoctor al researchers\, and other life science researchers from academia and indu stry who are interested in applying machine learning to omics data. No pre vious knowledge of machine learning is required\, but participants should be familiar with Python\, pandas data frames\, and basic statistics. X-ALT-DESC;FMTTYPE=text/html:

The Introduc tion to Machine Learning with Python course\, organised by SIB\, will take place on 1-2 October 2026 at the University of Bern\, Switzerland. T his two-day course will introduce participants to common machine learning (ML) methods and their application to omics data in biology and medicine. Through extensive hands-on exercises using Python and the scikit-learn ML framework\, participants will explore the main categories of machine learn ing\, learn how to select and implement appropriate algorithms\, and criti cally evaluate their use in omics studies. The course will also develop pr actical skills in interpreting and visualising the results of ML analyses using real-world biological and medical datasets.

Target aud ience
This course is particularly relevant for PhD students\, postdoctoral researchers\, and other life science researchers from academi a and industry who are interested in applying machine learning to omics da ta. No previous knowledge of machine learning is required\, but participan ts should be familiar with Python\, pandas data frames\, and basic statist ics.

X-MICROSOFT-CDO-ALLDAYEVENT:TRUE DTSTAMP:20260917T032314Z END:VEVENT BEGIN:VEVENT UID:6aab5d2261025 DTSTART;VALUE=DATE:20261002 SEQUENCE:0 TRANSP:OPAQUE DTEND;VALUE=DATE:20261003 SUMMARY:Introduction to Machine Learning with Python CLASS:PUBLIC DESCRIPTION:The Introduction to Machine Learning with Python course\, organ ised by SIB\, will take place on 1-2 October 2026 at the University of Ber n\, Switzerland. This two-day course will introduce participants to common machine learning (ML) methods and their application to omics data in biol ogy and medicine. Through extensive hands-on exercises using Python and th e scikit-learn ML framework\, participants will explore the main categorie s of machine learning\, learn how to select and implement appropriate algo rithms\, and critically evaluate their use in omics studies. The course wi ll also develop practical skills in interpreting and visualising the resul ts of ML analyses using real-world biological and medical datasets.Target audienceThis course is particularly relevant for PhD students\, postdoctor al researchers\, and other life science researchers from academia and indu stry who are interested in applying machine learning to omics data. No pre vious knowledge of machine learning is required\, but participants should be familiar with Python\, pandas data frames\, and basic statistics. X-ALT-DESC;FMTTYPE=text/html:

The Introduc tion to Machine Learning with Python course\, organised by SIB\, will take place on 1-2 October 2026 at the University of Bern\, Switzerland. T his two-day course will introduce participants to common machine learning (ML) methods and their application to omics data in biology and medicine. Through extensive hands-on exercises using Python and the scikit-learn ML framework\, participants will explore the main categories of machine learn ing\, learn how to select and implement appropriate algorithms\, and criti cally evaluate their use in omics studies. The course will also develop pr actical skills in interpreting and visualising the results of ML analyses using real-world biological and medical datasets.

Target aud ience
This course is particularly relevant for PhD students\, postdoctoral researchers\, and other life science researchers from academi a and industry who are interested in applying machine learning to omics da ta. No previous knowledge of machine learning is required\, but participan ts should be familiar with Python\, pandas data frames\, and basic statist ics.

X-MICROSOFT-CDO-ALLDAYEVENT:TRUE DTSTAMP:20260917T032314Z END:VEVENT END:VCALENDAR