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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\nYou should meet the learning outcomes of [First Steps with Python 
 in Life Sciences](https://www.sib.swiss/training/course/20250311_FSWP)\n a
 nd [Introduction to statistics with R](https://www.sib.swiss/training/cour
 se/20240122_STATR).\n\nFamiliarity with the Python programming language an
 d pandas data frames\, as well as a basic knowledge on statistics is requi
 red. Before applying to this course\, please assess your Python and statis
 tics skills using the quiz [here](https://forms.gle/ZpQFyHHwoPQKJSwv7).\n\
 nNo prior knowledge of ML concepts and methods is required. Knowledge of d
 ifferent omics data is recommended.\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://gith
 ub.com/sib-swiss/intro-machine-learning-training/blob/main/env_setup.md)(n
 ote: these instructions use [conda](https://docs.conda.io/projects/conda/e
 n/latest/user-guide/install/index.html) to manage the different packages) 
 \n\nPlease perform these installations PRIOR to the course and contact us 
 if you have any trouble. \n\n\n# Application\nThe registration fees for ac
 ademics are **200 CHF** and **1000 CHF** for for-profit companies. \n\nWhi
 le participants are registered on a first come\, first served basis\, exce
 ptions may be made to ensure diversity and equity\, which may increase the
  time before your registration is confirmed.\n\nApplications will close as
  soon as the places will be filled up\, until **22/09/2026**. Deadline for
  registration and free-of-charge cancellation is set is set to **22/09/202
 6**. Cancellation after this date will not be reimbursed. Please note that
  participation to 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 take place at t
 he University of Bern\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: Grégoire Rossier
 \, SIB Training Group  \n\nAt the end of the course\, we will provide a *C
 ertificate of Attendance* or a *Certificate of Achievement* recommending 0
 .5 ECTS credits (given a passed exam).\n\nYou are welcome to register to t
 he SIB courses mailing list to be informed of all future courses and works
 hops\, as well as all important deadlines using the form [here](https://li
 sts.sib.swiss/postorius/lists/courses.lists.sib.swiss/).\n\nPlease note th
 at participation in SIB courses is subject to our [general conditions](htt
 ps://www.sib.swiss/training/terms-and-conditions).\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/20261001_INMLP
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