Skip to content

Tutorials, links, and helpful tools to get started at CERN and in ATLAS

License

Notifications You must be signed in to change notification settings

YaleATLAS/YaleATLASTutorials

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 

Repository files navigation

Yale ATLAS Tutorials

This repository will contain a series of hands-on tutorials to get started with some of the basics of data handling and data analysis in ATLAS and at CERN.

These are intended for summer students joining our group, as well as group members coming from different fields, and people just getting started with programming.

Before you explore the material, it is necessary to get acquainted with some basic topics like Unix, Git/Github, Python and Machine Learning. Here are some links to free online courses, video-lectures and material you should look at if you're not familiar with some of these topics. These are my personal recommendations, but feel free to edit this document with other great online tutorials that you've found or used before.

Unix:

Git/Github

Python

  • Nice and thorough course on Coursera. It comes with 7 video lectures that should take you 30 minutes to 1 hour each; they are split up in shorter videos of a few minutes each. It also comes with assignments and exams if you want to get extra practice: https://class.coursera.org/programming1-002/lecture

  • Google Developers intro course. It comes with written instructions and material, as well as video lectures and exercises (see menu on the left): https://developers.google.com/edu/python/

  • Code Acedemy interactive course. Again, no videos, just super quick instructions and interactive shell. They estimate it should take 13 hours to complete. 2.5 million people took this course!: https://www.codecademy.com/learn/python

  • Here is a list of longer video courses on Coursera. They might take you too long though, so I would say only consider them if you plan to keep on watching a lecture a day for a few weeks. Mostly, I just wanted to leave these here for reference: https://www.coursera.org/courses?languages=en&query=python&start=0

Machine Learning

C++

For a more comprehensive list of resources and tutorials in all sorts of languages and frameworks, check out this list: https://github.com/WomenWhoCode/guidelines-resources/blob/master/learn_to_program.md

RooFit, RooStats, HistFactory

HistFitter

  • HistFitter: main page
  • HistFitter tutorial outside ATLAS: twiki
  • HistFitter advanced tutorial: twiki