BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260614T203145Z UID:ef0813c7-2833-4404-bdfe-cbf759e9c375 DTSTART:20241003T090000Z DTEND:20241004T170000Z 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 and 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 omics 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 / competencie s***\n\nNo prior knowledge of ML concepts and methods is required. \n\nKno wledge of different -omics data is recommended.\n\nFamiliarity with the Py thon programming language and pandas dataframes as well as a basic knowled ge on statistics is required. \n\nThe competences and knowledge levels req uired correspond to those taught in courses such as: [First Steps with Pyt hon in Life Sciences](https://www.sib.swiss/training/course/20240925_FSWP) and [Introduction to statistics with R](https://www.sib.swiss/training/co urse/20240122_STATR). \nTest your skills with Python and statistics with t he quiz [here](https://forms.gle/ZpQFyHHwoPQKJSwv7)\, before registering.\ n\n***Technical***\n\nYou will need to have a recent python3 as well as a number of python libraries installed. Please follow these [instructions to setup your environment ](https://github.com/sib-swiss/intro-machine-learn ing-training/blob/main/env_setup.md)(note: these instructions use [conda]( https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.ht ml) to manage the different packages) \n\nPlease perform these installatio ns PRIOR to the course and contact us if you have any trouble. \n\n\n# App lication\nThe registration fees for academics are **200 CHF** and **1000 C HF** for for-profit companies. \n\nWhile participants are registered on a first come\, first served basis\, exceptions may be made to ensure diversi ty and equity\, which may increase the time before your registration is co nfirmed.\n\nApplications will close as soon as the places will be filled u p\, until **16/09/2024**. Deadline for registration and free-of-charge can cellation is set is set to **19/09/2024**. Cancellation after this date wi ll not be reimbursed. Please note that participation to SIB courses is sub ject to our [general conditions](https://www.sib.swiss/training/terms-and- conditions).\n\nYou will be informed by email of your registration confirm ation. Upon reception of the confirmation email\, participants will be ask ed to confirm attendance by paying the fees within 5 days.\n\n# Venue and Time\nThis course will take place at the Kollegienhaus of the University o f Basel.\n\nThe course will start at 9:00 CEST and end around 17:00 CEST. \n\nPrecise information will be provided to the participants in due time.\ n\n# Additional information\nCoordination: Diana Marek\, SIB Training Gro up \n\nWe will recommend 0.50 ECTS credits for this course (given a passe d exam at the end of the course).\n\nYou are welcome to register to the SI B courses mailing list to be informed of all future courses and workshops\ , as well as all important deadlines using the form [here](https://lists.s ib.swiss/postorius/lists/courses.lists.sib.swiss/).\n\nPlease note that pa rticipation 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/events/code-of-conduct). Parti cipants of SIB courses are also required to abide by the same code.\n\nFor more information\, please contact [training@sib.swiss](mailto:training@si b.swiss). SUMMARY:Introduction to Machine Learning with Python URL;VALUE=URI:https://www.sib.swiss/training/course/20241003_INMLP END:VEVENT END:VCALENDAR