BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
BEGIN:VEVENT
DTSTAMP:20260705T021829Z
UID:62df3c7c-e24b-4479-8f36-e1f5c9e5ba8d
DTSTART:20241205T090000Z
DTEND:20241206T170000Z
DESCRIPTION:# Overview\nStatistics are an integral aspect of scientific res
 earch\, and in particular of life sciences that heavily rely on quantitati
 ve methodologies. Among other things\, statistics are an essential tool wh
 ich allows gaining new insights on the relationships between different bio
 logical measurements and variables. \n\nMachine learning (ML) also assists
  in making sense of large and complex datasets and can be very useful in m
 ining large biological datasets to uncover new insights that can advance t
 he field of bioinformatics.\n\nThis course was designed to guide participa
 nts in the exploration of the concepts of statistical modelling\, and at t
 he same time relate and contrast them with machine learning approaches whe
 n it comes to both classification and regression.\n\nA particular focus wi
 ll be given on the evaluation of the relevance of the produced models\, an
 d their interpretation in order to provide new biological knowledge.\n\n# 
 Audience\nThis course is addressed to life scientists who want to have a b
 etter understanding of these methods and on how to apply them to their own
  datasets. \n\n# Learning outcomes\nAt the end of the course\, the partici
 pants will be able to:\n * perform linear and logistic regressions\, and c
 ritically evaluate their results\n * describe the general Machine Learning
  data analysis pipeline\n * implement a classification task and appraise t
 he resulting model\n * contrast the statistical and Machine Learning appro
 aches when it comes to regression\, and choose the most appropriate to the
 ir question.\n\n\n# Prerequisites\n***Knowledge / competencies***\n\nThe c
 ourse is targeted to life scientists who are already familiar with the Pyt
 hon programming language and who have basic knowledge on statistics. The c
 ompetences and knowledge levels required correspond to those taught in cou
 rses such as: [First Steps with Python in Life Sciences](https://www.sib.s
 wiss/training/course/20240925_FSWP) and  [Introduction to statistics with 
 R](https://www.sib.swiss/training/course/20240122_STATR).\n\nBefore applyi
 ng to this course\, please self assess your Python and statistics skills u
 sing the quiz [here.](https://forms.gle/ZpQFyHHwoPQKJSwv7) \n\n\n***Techni
 cal***\n\nYou are required to have your own computer with an internet conn
 ection and the following tools installed PRIOR to the course:\nYou are req
 uired to have your own computer with an internet connection and the follow
 ing tools installed PRIOR to the course: [tools to be installed](https://g
 ithub.com/sib-swiss/statistics-and-machine-learning-training#pre-requisite
 s).\n\n\n\n# Schedule \n\nDay 1 \n* Warm-up: loading and plotting data wit
 h python. \n* Linear modelling: ordinary least squares\, from fitting to m
 odels comparison\n* Logistic regression and Generalized Linear Models (GLM
 ): from regression to classification\n\nDay 2 \n* The Machine Learning pip
 eline and evaluation\n* Machine Learning and classification: logistic regr
 ession classifier  and random forests\n* Machine Learning and regression\n
 \n# Application\n\n\n\nRegistration fees for academics are **200 CHF** and
  **1000 CHF** for for-profit companies. \n\nWhile participants are registe
 red on a first come\, first served basis\, exceptions may be made to ensur
 e diversity and equity\, which may increase the time before your registrat
 ion is confirmed.\n\nApplications will close as soon as the places will be
  filled up. Deadline for free-of-charge cancellation is set to **21/11/202
 4**. Cancellation after this date will not be reimbursed. Please note that
  participation in SIB courses is subject to our [general conditions](https
 ://www.sib.swiss/training/terms-and-conditions).\n\nYou will be informed b
 y email of your registration confirmation. Upon reception of the confirmat
 ion email\, participants will be asked to confirm attendance by paying the
  fees within 5 days.\n\n# Venue and Time\nThis course will ONLY take place
  in Zurich\, at the ETHZ campus\, IFW building. \n\n\n\nThe course will st
 art at 9:00 and end around 17:00 CET.\n\nPrecise information will be provi
 ded to the participants in due time.\n\n\n#  Additional information\n\nCoo
 rdination: Diana Marek\, SIB training group\, in collaboration with the [C
 hemistry | Biology | Pharmacy Information Center](https://chab.ethz.ch/en/
 the-department/services/infozentrum.html)\n\nHelper: Valentyn Bezshapkin\,
   Sunagawa Lab\, ETH Zürich\n\nWe will recommend 0.5 ECTS credits for thi
 s course (given a passed exam at the end of the course).\n\nYou are welcom
 e to register to the SIB courses mailing list to be informed of all future
  courses and workshops\, as well as all important deadlines using the form
  [here](https://lists.sib.swiss/postorius/lists/courses.lists.sib.swiss/).
 \n\nPlease note that participation in SIB courses is subject to our [gener
 al conditions](https://www.sib.swiss/training/terms-and-conditions).\n\nSI
 B abides by the [ELIXIR Code of Conduct](https://elixir-europe.org/events/
 code-of-conduct). Participants of SIB courses are also required to abide b
 y the same code.\n\nFor more information\, please contact [training@sib.sw
 iss](mailto://training@sib.swiss).\n\n\n\n![](\nhttps://infozentrum.ethz.c
 h/typo3conf/ext/theme/Resources/Public/Logos/logo-retina.png)
SUMMARY:Statistics and Machine Learning for Life Sciences
URL;VALUE=URI:https://www.sib.swiss/training/course/20241205_STAML
END:VEVENT
END:VCALENDAR