Addressing Large Hadron Collider Challenges by Machine Learning

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

  • The course is related to the online specialization ''Advanced Machine Learning"
  • Flexible Terms
  • 5 weeks (2 credits)
  • Time to completion: 24 hours
  • Certificate
Apply for the specialization

About the Course

In this online 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. 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

Course Objectives


Scrutinize the major stages of the data processing pipelines


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


Understand both the principles of the Experimental Physics and Machine Learning much better

Learning Outcomes

1. Know more about particle physics and experiments at CERN

2. Apply machine learning to particle identification

3. Understand comparison of two hypotheses through the measurement of some real-world parameters

4. Learn about Gaussian processes and Bayesian optimization

Course Syllabus

Week 1. Introduction into particle physics for data scientists

Week 2. Particle identification

Week 3. Search for New Physics in Rare Decays

Week 4. Search for Dark Matter Hints with Machine Learning at new CERN experiment

Week 5. Detector optimization

Andrei Ustyuzhanin

Head of Laboratory for Methods of Big Data Analysis: HSE Faculty of Computer

Mikhail Hushchyn

Researcher at Laboratory for Methods of Big Data Analysis: HSE Faculty of Computer Science


Course requires strong background in calculus, linear algebra, probability theory and machine learning

Graduation Document

Earn a Certificate upon completion



Learning Activities



Low-Stakes Assignments


High-Stakes Assignments

Final project

Cost and Conditions

21 000 ₽

Full access to the learning materials + Graduation document

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