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LICENSE (7048, 2022-01-04)
Project_1/ (0, 2022-01-04)
Project_1/IEdataset.csv (1354713, 2022-01-04)
Project_1/SED.bash (401, 2022-01-04)
Project_1/project1_slides.pdf (658245, 2022-01-04)
Session_1/ (0, 2022-01-04)
Session_1/BASH_session1_slides.pdf (108416, 2022-01-04)
Session_2/ (0, 2022-01-04)
Session_2/BASH_session2_slides.pdf (483695, 2022-01-04)
Session_2/makefiles_tea_tutorial.tar (20480, 2022-01-04)
Session_3/ (0, 2022-01-04)
Session_3/BASH_session3_slides.pdf (255564, 2022-01-04)
Session_3/if_condition_examples.sh (280, 2022-01-04)
Session_3/loop_simple_examples.sh (359, 2022-01-04)
Session_3/prepare_data_pipeline_for_a_specific_project.sh (3132, 2022-01-04)
Session_4/ (0, 2022-01-04)
Session_4/BASH_session4_slides.pdf (904018, 2022-01-04)
Session_4/tac.txt (34, 2022-01-04)

# BASH_workshop_2021 # BASH/SHELL Programming Workshop for Data Science 2021 Venue: Solbosch Campus of ULB, at Avenue Fr. Roosevelt, 42, 1050 Brussels (the Solvay building). Room: R42.3.103 Time:10-12AM. Speaker: Dr.Shruti Kulkarni -------------------------------------------------------------------------------------------------------------------------------------- ### 1.1 Why BASH for Data Science? Bash/Shell environment may not be the most ideal way to handle all kinds of data formats and it is often not the tool that comes to mind when we talk about data science! However, it is definitely useful and powerful in automating your workflows in a structured way. Sometimes, universities or institutional infrastructures often come with a pure Bash environment, such as what you get in the common linux based super-computers and you just want havea high-level view of the data before you drive into the real programming or other exploratory analysis, using Python, R and SQL, SAS, SPSS, and so on. Expertise in these data-science intensive languages can be time consuming. Whereas bash scripting is simple, easy to learn tool and might save some time in optimising a project. ### 1.2 Who this course is for? Anyone who wants to learn bash shell programming. Researchers who want to add Bash and other command line nifty tools to their bag of tricks. ### 1.3 What you’ll learn - Basics, the environment, other tools available to bash environment, practical tips. Basic bash commands and various features of bash sell. Advanced bash commands. Creating & running scripts to automate repeated tasks to save time. Tutorial: Makefiles, interplaying with bash scripts, and introduction to project structure. Tutorial: Manipulating and managing Github tasks in BASH environment. Tutorial: Data mining and wrangling in BASH environment. Use bash on processing real-world data sets. ### 1.4 Requirements or prerequisites - Desire to learn bash shell programming. Access to a Linux or Unix or Mac system (physical or virtual). ### 1.5 Getting started: Setup instructions for access to shell environment - Instructions * Install a linux OS, recommend Ubuntu, on a virtual machine on windows, such as virtualbox (or vmware) https://www.wikihow.com/Install-Ubuntu-on-VirtualBox This works well for those who have older Windows versions. * *It is recommended to install WSL (windows subsystem for linux) on Windows 10. It allows you to install Ubuntu on windows, in a limited way, but enough to give you access to bash shell right in your Windows environment.* * Create AWS account – Free tier, Create EC2 instance, SSH (Possible with azure too). * Optional – GIT BASH, Atom editor (very limited features, not recommended). For set up instructions please refer to the repo and slides.

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