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DTSTAMP:20260718T045936Z
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DESCRIPTION:# Overview\nPython is an open-source and general-purpose script
 ing language which runs on all major operating systems. It was designed to
  be easily read and written with comparatively simple syntax. Over the rec
 ent years Python has become a programming language of choice for bioinform
 atics and data analysis\, and in particular for applications that make use
  of machine learning or deep learning. However\, these applications usuall
 y require a good mastering of a few modules (such as numpy\, or pandas) th
 at can go beyond basic Python commands. This 1-day course is an introducti
 on to modules (mainly pandas and seaborn) and recipes to unlock the potent
 ial of Python for day-to-day data exploration and analysis of real-life da
 tasets.\n\nTopics that will be covered in this course include:\n* Parsing\
 , transforming\, and exporting data using pandas\n* Exploring data\, and c
 reating useful summaries using pandas and numpy\n* Representing data in an
  efficient and impactful manner using seaborn\n\n# Audience\n\nThis course
  is designed for PhD students\, postdoctoral and other researchers in the 
 life sciences from both academia and industry who are familiar with writin
 g Python code and core Python elements and would like to explore it furthe
 r in their daily data wrangling and exploration tasks.\n\n# Learning outco
 mes\nAt the end of this course\, participants are expected to:\n* **Execut
 e** parsing into any tabulated data set in a couple of lines \n* **Summari
 ze** and **execute** quality control on their data \n* **Execute** a filte
 r\, sub-sample or aggregation of specific parts of their dataset(s) \n* **
 Develop** clear visual representations to explore data and communicate the
 ir findings \n\n\n# Prerequisites\n***Knowledge / competencies***\n\nThe c
 ourse is targeted to life scientists\, bioinformaticians\, and researchers
  who are already familiar with the Python programming language and who hav
 e basic knowledge in statistics. Competences and knowledge levels required
  correspond to those taught in courses such as: [First Steps with Python i
 n Life Sciences](https://www.sib.swiss/training/course/20250917_FSWP) and 
 [Introduction to statistics with R](https://www.sib.swiss/training/course/
 20250127_STATR).\n**Test your skills with Python and statistics with [the 
 quiz here](https://forms.gle/iCydNS8LUUkm7csz7)\, before registering. We r
 ecommend 4 out of 6 correct answers.**\n\nA few days before the course\, r
 egistered participants will receive a small "warm-up" jupyter notebook to 
 go through. This will be in order to help them get a quick refresher on th
 eir python know-how and check that all libraries are working properly. \n\
 n\n***Technical***\n\nYou are required to use your own laptop\, with a rec
 ent Python 3 version. \nPlease make sure you have install Anaconda\, Jupyt
 er notebook and the needed Python librairies on your personal laptop befor
 e the start of the course.\nYou can find all the information for the prere
 quisiste installation [here](https://github.com/sib-swiss/intermediate-pyt
 hon-training#prerequisite-installation).\n\n\n# Application\n\n\nRegistrat
 ion fees for academics are **100 CHF** and **500 CHF** for for-profit comp
 anies. \n\nWhile participants are registered on a first come\, first serve
 d basis\, exceptions may be made to ensure diversity and equity\, which ma
 y increase the time before your registration is confirmed.\n\nApplications
  will close on **02/04/2026** or as soon as the places will be filled up. 
 Deadline for free-of-charge cancellation is set to **31/03/2026**. Cancell
 ation after this date will not be reimbursed. \n\nYou will be informed by 
 email of your registration confirmation. Upon reception of the confirmatio
 n email\, participants will be asked to confirm attendance by paying the f
 ees within 5 days.\n\n# Venue and Time\nThis course will be streamed using
  Zoom.\n\nThe course will start at 9:00 and end around 17:00 CET.\n\nPreci
 se information will be provided to the participants in due time.\n\n#  Add
 itional information\nCoordination: Valeria Di Cola\, SIB Training Group.\n
 \nWe will 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 cour
 ses mailing list to be informed of all future courses and workshops\, as w
 ell as all important deadlines using the form [here](https://lists.sib.swi
 ss/postorius/lists/courses.lists.sib.swiss/).\n\nPlease note that particip
 ation in SIB courses is subject to our [general conditions](https://www.si
 b.swiss/training/terms-and-conditions).\n\nSIB abides by the [ELIXIR Code 
 of Conduct](https://elixir-europe.org/events/code-of-conduct). Participant
 s of SIB courses are also required to abide by the same code.\n\nFor more 
 information\, please contact [training@sib.swiss](mailto://training@sib.sw
 iss).
SUMMARY:Data Analysis and Representation in Python
URL;VALUE=URI:https://www.sib.swiss/training/course/20260414_DARPY
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