Mastering the Terminal with Bash and Unix (September 2024)

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A 2-day workshop on the Bash shell and terminal command line tools, scripts, and pipelines for data analysis

 

Knowledge on how to use a terminal command line is an essential skill, not just for data scientists, but for any biomedical researcher who needs to work with large datasets, including registry data, clinical datasets and high-throughput biological data. 

In combination with the basics of bash, mastering the command line will allow you to wrangle large datasets and run command line softwares for data analysis, including  those for sequence alignment, gene annotation, SNP & CNV calling, web-scraping, protein structure analysis, and much much more.

Additionally, you will build the skill set you need to work on high performance computer (HPC) systems and external servers, when the power of your local machine does not suffice.

 

This is a 2-day introductory workshop to the Bash shell and command line interpreter.
In the workshop, we will take you though:

1. Understanding what a terminal is, how to use it, how to get help and handle errors
2. Setting up a good directory structure for computational projects
3. Performing basic unix operations on files
4. Automating workflow through scripts and workflow language
5. Navigating on unix-based HPC environments (servers) such as computerome 2.0

 

Interested?

➡️ If you are an employee, sign up here

➡️ If you are a PhD student, sign up here

 

Course Disclaimers: 
      • The course is free of charge and intended for all KU researchers, and especially PhD students, at SUND
      • A no-show free will be implemented for registrants who do not attend the course
      • If you are a PhD student and you would like to receive ECTS credits for participating in this course, you must enroll through the PhD school school system
      • If you are not a PhD student and sign up via the PhD school registration link, you will be charged for the course
      • Please be advised that course participation via the PhD school happens under the PhD school's terms and conditions which HeaDS has no influence over