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DTSTART:20250519T090000Z
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DESCRIPTION:## Overview\nLarge Language Models (LLMs) are creating a shift 
 of paradigm in how we interact with data across domains. Bioinformatics is
  one of the fields most prominently impacted by the advent of LLMs\, wheth
 er for biodata exploration\, via [LLM-based AI assistants](https://www.bio
 rxiv.org/content/10.1101/2024.01.31.578275v1)\, towards enabling full scie
 ntific discovery pipelines via [novel agentic assistants](https://research
 .google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist
 /). But how are these models trained? How do we choose among the plethora 
 of options for a target use case? And how do we adapt an existing model to
  our needs?\n\nThis one-day course will give a gentle introduction into LL
 Ms\, going from theoretical concepts towards practical\, hands-on experien
 ce interacting with LLMs for exploring biodata through a series of exercis
 es provided in Jupyter Notebooks. These will include programmatically inte
 racting with an LLM to construct a simple Retrieval Augmented Generation (
 RAG) application for answering biological questions using existing SIB res
 ources.\n\n## Audience\nThis course is addressed to life scientists and bi
 oinformaticians\, in academia and industry\, who are interested in LLMs an
 d who already have prior experience using Python through Jupyter Notebooks
 .\n\n## Learning outcomes\nAt the end of the course\, the participants are
  expected to:\n* Understand the basics of Large Language Models\n* List so
 me existing LLMs and their applications in bioinformatics \n* Programmatic
 ally interact with LLMs in Jupyter Notebooks (Python)\n* Build a simple RA
 G application for answering questions over biodata\n\n\n## Prerequisites\n
 ##### Knowledge / competencies\nThis course is designed for beginners. Par
 ticipants are expected to have at least one year experience with Python (i
 ntermediate level).\n\n##### Technical\nYou are required to bring your own
  computer with an Internet connection and a recent version of Python (3.12
  or higher) installed. Optionally you can also have Jupyter Notebook insta
 lled.\n\n\n## Application\n\n\nThe registration fees for academics are **1
 00 CHF** and **500 CHF** for for-profit companies. \n\nWhile participants 
 are registered on a first come\, first served basis\, exceptions may be ma
 de to ensure diversity and equity\, which may increase the time before you
 r registration is confirmed. \n\nApplications will close as soon as the pl
 aces will be filled up\, but not later than **05/05/2025**. Deadline for f
 ree-of-charge cancellation is set to **05/05/2025**. Cancellation after th
 is date will not be reimbursed. \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\nThis course will take place at the University o
 f Lausanne. \n\nIt will start at 9:00 CEST and end around 17:00 CEST.\n\nP
 recise information will be provided to the participants before the course.
 \n\n## Additional information\nCoordination: Diana Marek\, SIB Training gr
 oup.\n\nHelper: Panayiotis Smeros\, Vital-IT group\n\n\nWe will recommend 
 0.25 ECTS credits for this course (given a passed exam at the end of the c
 ourse). \n\nYou are welcome to register to the SIB courses mailing list to
  be informed of all future courses and workshops\, as well as all importan
 t deadlines using the form [here](https://lists.sib.swiss/postorius/lists/
 courses.lists.sib.swiss/).\n\nPlease note that participation in SIB course
 s is subject to our [general conditions](https://www.sib.swiss/training/te
 rms-and-conditions).\n\nSIB abides by the [ELIXIR Code of Conduct](https:/
 /elixir-europe.org/events/code-of-conduct). Participants of SIB courses ar
 e also required to abide by the same code.\n\nFor more information\, pleas
 e contact [training@sib.swiss](mailto://training@sib.swiss).
SUMMARY:Using Large Language Models for Biodata Exploration: From Theory to
  Practice
URL;VALUE=URI:https://www.sib.swiss/training/course/20250519_USLLM
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