BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260808T155407Z UID:30d647fb-89fc-4366-a27f-5efed44eaad2 DTSTART:20241107T000000Z DTEND:20241108T000000Z DESCRIPTION:# Overview\nThis course aims to give the participants some prac tical knowledge of deep learning models in life sciences. \n\nWith the ris e of new technologies\, the volume of omics data in biology and medicine h as grown exponentially recently. A major issue is to mine useful predictiv e knowledge from these data. Machine learning (ML) is a discipline in whic h computer algorithms perform automated learning by using data to assist h umans in dealing with a large volume of multidimensional data\, and deep l earning is one of these methods. Deep learning is based on artificial neur al networks inspired by the structure and function of the human brain. It has been widely applied in computer vision\, natural language processing\, computational biology\, etc.\n\nThis course will not make the participant an absolute expert in the complex and dynamic world of Deep-Learning. Sti ll\, it will aim to “break the ice” through the implementation of simp le yet concrete\, deep-learning models using the PyTorch library. Particip ants will be introduced to the basic building blocks of deep-learning mode ls and the main parameters tuned and monitored to ensure the training of l arge models.\n\n\n# Audience\nThis course is aimed at PhD students\, post- docs and researchers in life sciences who already know about Machine Learn ing and would like to start practising Deep Learning with PyTorch.\n\n\n# Learning outcomes\nAt the end of the course\, the participants will be abl e to:\n* Create simple deep-learning models\n* Train\, and evaluate a deep -learning auto-encoder model \n* Adapt a pre-existing deep-learning model to a new task using fine-tuning\n\n\n# Prerequisites\n##### Knowledge / co mpetencies required\n\n* The deep-learning concepts discussed in the cours e “[Deep learning - fundamentals - Nov 6\, 2023](https://www.sib.swiss/t raining/course/20231106_DLFLS)”. In particular\, the following two the l essons are mandatory and should be seen before the course starts: ["Introd uction to Deep Learning"](https://www.youtube.com/watch?v=R9t0JCTB30w&\ ;list=PLoCxWrRWjqB0UEzMo-ZEmNoHHmLfKd43h&\;index=1&\;t=2s&\;pp=iA QB) and ["Deep Learning Techniques in Life Sciences"](https://www.youtube. com/watch?v=VXNyeBZGbUM&\;list=PLoCxWrRWjqB0UEzMo-ZEmNoHHmLfKd43h&\; index=2&\;t=5s&\;pp=iAQB). \n* A good fluency with the Python progra mming language\, including working knowledge of common data analysis libra ries such as numpy\, panda\, matplotlib or scikit-learn.\n* Familiarity wi th different omics data technologies (highly recommended).\n\n##### Techni cal\nThe needed libraries will be indicated in the course GitHub repo and here in due time.\n\n\n\n# Application\nThe registration fees for academic s are **150 CHF** and **750 CHF** for for-profit companies.\n\nWhile parti cipants may be registered on a first come\, first served basis\, exception s may be made to ensure diversity and equity\, which may increase the time before your registration is confirmed.\n\nYou will be informed by email o f your registration confirmation. Upon reception of the confirmation email \, participants will be asked to confirm attendance by paying the fees wit hin 5 days.\n\nApplications close on *10/10/2024* or as soon as the course is full. Deadline for free-of-charge cancellation is set to *25/10/2024*. Cancellation after this date will not be reimbursed. Please note that par ticipation in SIB courses is subject to our [general conditions](https://w ww.sib.swiss/training/terms-and-conditions).\n\n# Venue and Time\nThis cou rse will be streamed. \n\nThe course will start at 9:00 and end around 17: 00. \n\nPrecise information will be provided to the participants in due ti me.\n\n\n# Additional information\nCoordination: Patricia Palagi\n\nWe wi ll recommend 0.25 ECTS credits for this course (given a passed exam at the end of the course).\n\nYou are welcome to register to the SIB courses mai ling list to be informed of all future courses and workshops\, as well as all important deadlines using the form [here](https://lists.sib.swiss/post orius/lists/courses.lists.sib.swiss/).\n\nPlease note that participation i n SIB courses is subject to our [general conditions](https://www.sib.swiss /training/terms-and-conditions).\n\nSIB abides by the [ELIXIR Code of Cond uct](https://elixir-europe.org/events/code-of-conduct). Participants of SI B courses are also required to abide by the same code.\n\nFor more informa tion\, please contact [training@sib.swiss](mailto://training@sib.swiss). SUMMARY:Practical dip into deep learning - a PyTorch short crash-course URL;VALUE=URI:https://www.sib.swiss/training/course/20241108_PRDIP END:VEVENT END:VCALENDAR