BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260306T004225Z UID:51232282-6b54-4286-bc77-8b707c3cbe7c DTSTART:20260331T090000Z DTEND:20260401T170000Z DESCRIPTION:**A certain number of places will be attributed in priority to CUSO members.**\n\n\n\n# Overview\nStatistics are an integral aspect of sc ientific research\, and in particular of life sciences that heavily rely o n quantitative methodologies. Among other things\, statistics are an essen tial tool which allows gaining new insights on the relationships between d ifferent biological measurements and variables. \n\nMachine learning (ML) also assists in making sense of large and complex datasets and can be very useful in mining large biological datasets to uncover new insights that c an advance the field of bioinformatics.\n\nThis course was designed to gui de participants in the exploration of the concepts of statistical modellin g\, and at the same time relate and contrast them with machine learning ap proaches when it comes to both classification and regression.\n\nA particu lar focus will be given on the evaluation of the relevance of the produced models\, and their interpretation in order to provide new biological know ledge.\n\n# Audience\nThis course is addressed to life scientists who want to have a better 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 participants will be able to:\n * perform linear and logistic regress ions\, and critically evaluate their results\n * describe the general Mach ine Learning data analysis pipeline\n * implement a classification task an d appraise the resulting model\n * contrast the statistical and Machine Le arning approaches when it comes to regression\, and choose the most approp riate to their question.\n\n\n# Prerequisites\n***Knowledge / competencies ***\n\nFamiliarity with the Python programming language and pandas data fr ames\, as well as a basic knowledge on statistics is required.\n\nYou shou ld meet the learning outcomes of [First Steps with Python in Life Sciences ](https://www.sib.swiss/training/course/20250311_FSWP)\n and [Data Analysi s and Representation in Python](https://www.sib.swiss/training/course/2025 1110_DARPY)\, as well as [Introduction to statistics with R](https://www. sib.swiss/training/course/20260126_STATR) for the statistics part.\n\n\nBe fore applying to this course\, please assess your Python and statistics sk ills using the quiz [here](https://forms.gle/ZpQFyHHwoPQKJSwv7).\n\nNo pri or knowledge of ML concepts and methods is required.\n\n***Technical***\n\ nYou are required to have your own computer with an internet connection an d the following tools installed PRIOR to the course:\nYou are required to have your own computer with an internet connection and the following tools installed PRIOR to the course: [tools to be installed](https://github.com /sib-swiss/statistics-and-machine-learning-training#pre-requisites).\n\nAl though not mandatory\, we also highly recommend you to use the same comput er to connect to the zoom classroom and perform the exercises\, otherwise we will have difficulties helping you debug your code.\n\n# Schedule \n\nD ay 1 \n* Warm-up: loading and plotting data with python. \n* Linear modell ing: ordinary least squares\, from fitting to models comparison\n* Logisti c regression and Generalized Linear Models (GLM): from regression to class ification\n\nDay 2 \n* The Machine Learning pipeline and evaluation\n* Mac hine Learning and classification: logistic regression classifier and rand om forests\n* Machine Learning and regression\n\n# Application\n\n\n\nRegi stration fees for academics are **200 CHF** and **1000 CHF** for for-profi t companies. \n\nWhile participants are registered on a first come\, first served basis\, exceptions may be made to ensure diversity and equity\, wh ich may increase the time before your registration is confirmed.\n\nApplic ations will close as soon as the places will be filled up. Deadline for fr ee-of-charge cancellation is set to **17/03/2026**. Cancellation after thi s date will not be reimbursed. Please note that participation in SIB cours es is subject to our [general conditions](https://www.sib.swiss/training/t erms-and-conditions).\n\nYou will be informed by email of your registratio n confirmation. Upon reception of the confirmation email\, participants wi ll be asked to confirm attendance by paying the fees within 5 days.\n\n# V enue and Time\n\nThis course will be streamed.\n\nThe course will start at 9:00 and end around 17:00 CET.\n\nPrecise information will be provided to the participants in due time.\n\n\n# Additional information\n\nCoordinat ion: Grégoire Rossier\, SIB training group.\n\n\nAt the end of the course \, we will provide a *Certificate of Attendance* or a *Certificate of Achi evement* recommending 0.5 ECTS credits (given a passed exam).\n\nYou are w elcome to register to the SIB courses mailing list to be informed of all f uture courses and workshops\, as well as all important deadlines using the form [here](https://lists.sib.swiss/postorius/lists/courses.lists.sib.swi ss/).\n\nPlease note that participation in SIB courses is subject to our [ general conditions](https://www.sib.swiss/training/terms-and-conditions).\ n\nSIB abides by the [ELIXIR Code of Conduct](https://elixir-europe.org/ev ents/code-of-conduct). Participants of SIB courses are also required to ab ide by the same code.\n\nFor more information\, please contact [training@s ib.swiss](mailto://training@sib.swiss). SUMMARY:Statistics and Machine Learning for Life Sciences URL;VALUE=URI:https://www.sib.swiss/training/course/20260331_STAML END:VEVENT END:VCALENDAR