BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260615T173039Z UID:7a115c9d-2dc6-45f1-a42a-35b9b7993e59 DTSTART:20220616T090000Z DTEND:20220617T170000Z DESCRIPTION:# Overview\nWith the rise of new technologies\, the volume of o mics data in the fields of biology and medicine has grown exponentially in recent times and a major issue is to mine useful predictive knowledge fro m these data. Machine learning (ML) is a discipline in which computer algo rithms perform automated learning by using data in order to assist humans to deal with the large volume of multidimensional data. The analysis of su ch data is not trivial and ML is a necessary tool to extract knowledge an d make predictions that can advance the field of bioinformatics.\n\nThis 2 -day course will introduce participants to common ML algorithms and teach how to apply them to omics data in extensive practical sessions. The pract ical sessions will be conducted in Python3 based on the widely applied sci kit-learn ML framework. The course will comprise a number of hands-on exer cises and challenges where the participants will acquire a first understan ding of the standard ML methods and processes\, as well as the practical s kills in applying them to real world problems using publicly available bio logical or medical data sets.\n\n# Audience\nThis course is intended for PhD students\, post-docs and staff scientists who are interested in applyi ng ML to analyze these data.\n\n# Learning objectives\nAt the end of the c ourse\, the participants are expected to:\n* Understand the ML taxonomy an d the commonly used machine learning algorithms for analysing “omics” data\n* Understand differences between ML approaches and in which situatio ns they can be applied\n* Understand and critically evaluate applications of ML in omics studies\n* Learn how to implement common ML algorithms usin g the scikit-learn Python framework \n* Interpret and visualize the result s obtained from ML analyses\n\n# Prerequisites\n##### Knowledge / competen cies\nNo prior knowledge of ML concepts and methods is required. \n\nKnowl edge of different -omics data is recommended.\n\nFamiliarity with the Pyth on programming language as well as a basic knowledge on statistics is requ ired. \n\nThe competences and knowledge levels required correspond to thos e taught in courses such as: [First Steps with Python in Life Sciences](ht tps://www.sib.swiss/training/course/20210929_PYTFS)\, [Introduction to sta tistics with Python](https://www.sib.swiss/training/course/20210621_STATP) and [Introduction to statistics with R](https://www.sib.swiss/training/co urse/2021-02-intro-stats). \nTest your skills with Python and statistics w ith the quiz [here](https://forms.gle/ZpQFyHHwoPQKJSwv7)\, before register ing.\n\n##### Technical\nYou are required to have your own computer with a n Internet connection and the following tools installed PRIOR to the cours e:\n\n* latest Python 3 distribution\, preferably bundled using [conda](ht tps://docs.continuum.io/anaconda/install/) \n* [Jupyter](https://jupyter.o rg/install)\n* the [scipy](https://www.scipy.org/install.html) library (NB : if you installed conda\, then this library is already installed)\n* [sci kitLearn](https://scikit-learn.org/stable/install.html) \n\nThere will be access to the eduroam and guest-unil networks.\n\n\n\n# Application\nThe r egistration fees for academics are **120 CHF** and **600 CHF** for for-pro fit companies. While participants are registered on a first come\, first s erved basis\, exceptions may be made to ensure diversity and equity\, whic h may increase the time before your registration is confirmed.\n\nYou will be informed by email of your registration confirmation. Upon reception of the confirmation email\, participants will be asked to confirm attendance by paying the fees within 5 days.\n\nDeadline for registration and free-o f-charge cancellation is set is set to **09/06/2022**. Cancellation after this date will not be reimbursed. Please note that participation to SIB co urses is subject to our [general conditions](https://www.sib.swiss/trainin g/terms-and-conditions).\n\n# Venue and Time\nThe course will take place * *in person only** at the University of Lausanne (Metro M1 line\, Sorge st ation). It will NOT be streamed simulataneously. It will start at 9:00 CET and end around 17:00 CET. \n\nPrecise information will be provided to the participants in due time.\n\n# Additional information\nCoordination: Mon ique Zahn\, SIB Training Group.\n\nWe will recommend 0.50 ECTS credits for this course (given a passed exam at the end of the course).\n\nYou are we lcome to register to the SIB courses mailing list to be informed of all fu ture courses and workshops\, as well as all important deadlines using the form [here](https://lists.sib.swiss/mailman/listinfo/courses).\n\nSIB abid es by the [ELIXIR Code of Conduct](https://elixir-europe.org/events/code-o f-conduct). Participants of SIB courses are also required to abide by the same code.\n\nFor more information\, please contact [training@sib.swiss](m ailto:training@sib.swiss). LOCATION:SIB SUMMARY:Introduction to Machine Learning with Python URL;VALUE=URI:https://www.sib.swiss/training/course/20220616_INMLP END:VEVENT END:VCALENDAR