PHYS-815 / 4 credits

Teacher: Various lecturers

Language: English

Remark: July 15 to 30th 2021 The school will be held online. The details and registration are available at the link: https://indico.cern.ch/event/1025052/


Frequency

Every year

Summary

The school will cover the relatively young area of data analysis and computational research that has started to emerge in High Energy Physics (HEP). It is known by several names including "Multivariate Analysis", "Neural Networks", "Classification/Clusterization techniques"

Content

Note

School materials will be available on github.

Learning Prerequisites

Required courses

python programming experience (e.g. http://nbviewer.jupyter.org/gist/rpmuller/5920182, https://www.codecademy.com/learn/learn-python)

Learning Outcomes

By the end of the course, the student must be able to:

  • formulate a HEP-related problem in ML-friendly terms
  • select quality criteria for a given problem

In the programs

  • Exam form: During the semester (session free)
  • Subject examined: 7th Machine learning in HEP Summer School
  • Lecture: 54 Hour(s)
  • Exercises: 28 Hour(s)

Reference week