BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260618T131252Z UID:a36e619c-0e56-4114-9b69-4e1a2c800da2 DTSTART:20250526T090000Z DTEND:20250526T170000Z DESCRIPTION:Please note that this 2-day course will be streamed over 4 half -days\, in the afternoon of the following dates:\n* 26 May 2025\n* 2 June 2025\n* 16 June 2025\n* 23 June 2025\n\n\n# Overview\nWith the rise of new technologies\, the volume of omics data in biology and medicine has grown exponentially recently. A significant issue is to mine useful predictive knowledge from these data. Machine learning (ML) is a discipline in which computer algorithms perform automated learning by using data to assist hum ans in dealing with large volumes of multidimensional data. The analysis o f such data is not trivial\, and ML is a necessary tool to extract knowled ge and make predictions that can advance the field of bioinformatics.\n\nT his 2-day course will introduce participants to common ML algorithms and h ow to apply them to omics data in extensive practical sessions. The practi cal sessions will be conducted in Python3 based on the widely applied scik it-learn ML framework. The course will comprise a number of hands-on exerc ises and challenges where the participants will acquire a first understand ing of the standard ML methods and processes\, as well as the practical sk ills in applying them to real world problems using publicly available biol ogical or medical data sets. \n\n# Audience\nThis course is intended for P hD students\, post-docs and staff scientists who are interested in applyin g ML to analyze these data.\n\n# Learning objectives\nAt the end of the co urse\, the participants are expected to:\n* Explain the ML taxonomy and th e commonly used machine learning algorithms for analysing omics data\n* De scribe differences between ML approaches and in which situations they can be applied\n* Critically evaluate applications of ML in omics studies\n* I mplement common ML algorithms using the scikit-learn Python framework \n* Interpret and visualize the results obtained from ML analyses\n\n# Prerequ isites\n### ***Knowledge / competencies***\nYou should meet the learning o utcomes of [First Steps with Python in Life Sciences](https://www.sib.swis s/training/course/20250311_FSWP)\n and [Introduction to statistics with R] (https://www.sib.swiss/training/course/20240122_STATR).\n\nFamiliarity wit h the Python programming language and pandas data frames\, as well as a ba sic knowledge on statistics is required. Before applying to this course\, please assess your Python and statistics skills using the quiz [here](http s://forms.gle/ZpQFyHHwoPQKJSwv7).\n\nNo prior knowledge of ML concepts and methods is required. Knowledge of different omics data is recommended.\n\ n### ***Technical***\nThis course will be streamed\, you are thus required to have your own computer with an Internet connection.\n\nAdditionally\, you will need to have a recent python3 as well as a number of python libra ries installed. Please follow these [instructions to setup your environmen t ](https://github.com/sib-swiss/intro-machine-learning-training/blob/main /env_setup.md)(note: these instructions use [conda](https://docs.conda.io/ projects/conda/en/latest/user-guide/install/index.html) to manage the diff erent packages) \n\nPlease perform these installations PRIOR to the course and contact us if you have any trouble. \n\nFinally\, although not mandat ory\, we also highly recommend you to use the same computer to connect to the zoom classroom and perform the exercises\, otherwise we will have diff iculties helping you debug your code. \n\n# Application\nThe registration fees for academics are **200 CHF** and **1000 CHF** for for-profit compani es.\n\nWhile participants are registered on a first come\, first served ba sis\, exceptions may be made to ensure diversity and equity\, which may in crease the time before your registration is confirmed.\n\nApplications wil l close on **12/05/2025** or as soon as the places will be filled up. Dead line for free-of-charge cancellation is set to **12/05/2025**. Cancellatio n after this date will not be reimbursed. Please note that participation t o SIB courses is subject to our [general conditions](https://www.sib.swiss /training/terms-and-conditions).\n\nYou will be informed by email of your registration confirmation. Upon reception of the confirmation email\, part icipants will be asked to confirm attendance by paying the fees within 5 d ays.\n\n# Venue and Time\nPlease note that this 2-day course will be strea med over 4 half-days\, from 14:00 to 17:30 CET of the following dates:\n* 26 May 2025\n* 2 June 2025\n* 16 June 2025\n* 23 June 2025\n\nMore informa tion will be provided to the registered participants one week before the c ourse starts. \n\n# Additional information\nCoordination: Monique 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 welcome to reg ister 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/mailman/listinfo/courses).\n\nSIB abides by the [E LIXIR Code of Conduct](https://elixir-europe.org/events/code-of-conduct). Participants of SIB courses are also required to abide by the same code.\n \nFor more information\, please contact [training@sib.swiss](mailto:traini ng@sib.swiss). SUMMARY:Introduction to Machine Learning with Python URL;VALUE=URI:https://www.sib.swiss/training/course/20250526_INMLP END:VEVENT END:VCALENDAR