Back to Addressing Large Hadron Collider Challenges by Machine Learning
Addressing Large Hadron Collider Challenges by Machine Learning, National Research University Higher School of Economics
4.9
19 ratings
About this Course
The Large Hadron Collider (LHC) is the largest data generation machine for the time being. It doesn’t produce the big data, the data is gigantic. Just one of the four experiments generates thousands gigabytes per second. The intensity of data flow is only going to be increased over the time. So the data processing techniques have to be quite sophisticated and unique. In this course we’ll introduce students into the main concepts of the Physics behind those data flow so the main puzzles of the Universe Physicists are seeking answers for will be much more transparent. Of course we will scrutinize the major stages of the data processing pipelines, and focus on the role of the Machine Learning techniques for such tasks as track pattern recognition, particle identification, online real-time processing (triggers) and search for very rare decays. The assignments of this course will give you opportunity to apply your skills in the search for the New Physics using advanced data analysis techniques. Upon the completion of the course you will understand both the principles of the Experimental Physics and Machine Learning much better.
Top reviews
By WX
•Oct 17, 2018
nice starting point for graduate students or senior undergraduate students who want to dig deeper in this direction
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2 Reviews
By Wei Xie
•Oct 17, 2018
nice starting point for graduate students or senior undergraduate students who want to dig deeper in this direction
By Shanaya Mehta
•Aug 30, 2018
For an undergrad student of computer science, this course provides great insights into the world of astrophysics and how machine learning can be applied to solve some of the greatest mysteries of the universe.
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