À propos de ce cours
4.9
14 notes
2 avis
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....
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Advanced Level

Niveau avancé

Clock

Approx. 15 hours to complete

Recommandé : 5 weeks of study...
Comment Dots

English

Sous-titres : English...
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Advanced Level

Niveau avancé

Clock

Approx. 15 hours to complete

Recommandé : 5 weeks of study...
Comment Dots

English

Sous-titres : English...

Programme du cours : ce que vous apprendrez dans ce cours

Week
1
Clock
4 heures pour terminer

Introduction into particle physics for data scientists

This module starts with a mild introduction into particle physics, and it explains basic notions, so you will understand the structure and the principal terms that physicists are using to describe the forces and particles that comprise the fundamental level of our universe. Also, we'll describe main stages of data collection and analysis that happens at LHC experiment. Each step is associated with specific machine learning challenges and some of which we are going to cover later. The final part of the module describes a very high-level example of data analysis that shows how simple data analysis techniques can be used for discovery of an elementary particle....
Reading
4 vidéos (Total 45 min), 2 lectures, 1 quiz
Video4 vidéos
Experimental particle physics13 min
Testing hypotheses experimentally12 min
Particle physics simulation7 min
Reading2 lectures
Pre-course survey10 min
Lecture slides10 min
Week
2
Clock
5 heures pour terminer

Particle identification

This module is about detectors in high energy physics. It describes several detector designs, different detector systems, how they work and what particle parameters they measure. Several cases in high energy physics where machine learning can be successfully applied are demonstrated....
Reading
7 vidéos (Total 62 min), 1 lecture, 2 quiz
Video7 vidéos
Tracking system7 min
Ring Imaging Cherenkov detector6 min
Calorimeters11 min
Muon system8 min
Machine learning in particle identification6 min
Uniform classifiers12 min
Reading1 lecture
Lecture slides10 min
Quiz1 exercice pour s'entraîner
Particle identification quiz20 min
Week
3
Clock
7 heures pour terminer

Search for New Physics in Rare Decays

In this module, we explain how new physics search can be mediated through a search for rare processes. We describe the main steps physicists have to follow to find rare decay. At first search for such phenomena may look like a perfect task for machine learning algorithms. However, there are several constraints that one have to keep in mind during training and application of a classifier....
Reading
4 vidéos (Total 41 min), 1 lecture, 1 quiz
Video4 vidéos
Lepton Flavour Violation14 min
Classifier Constraints12 min
Data vs Simulation Agreement5 min
Reading1 lecture
Lecture slides10 min
Week
4
Clock
4 heures pour terminer

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

We start this module with explanation what Dark Matter phenomenon is about and what are the general strategies for Dark Matter search. Then we boil down the topic towards one of the CERN proposed experiments - SHiP. Given the design of the experiment, we consider the signatures that Dark Matter particles may produce. Of course, Machine Learning algorithms can be applied to discriminate such signatures from the background. We'll see how clustering algorithms can improve the signal visibility even further....
Reading
5 vidéos (Total 41 min), 1 lecture, 1 quiz
Video5 vidéos
Search for Dark Matter at Accelerator Experiment11 min
Getting Data Before Experiment is built10 min
Going Deeper9 min
Looking Ahead3 min
Reading1 lecture
Lecture slides10 min
4.9

Meilleurs avis

par WXOct 17th 2018

nice starting point for graduate students or senior undergraduate students who want to dig deeper in this direction

Enseignants

Andrei Ustyuzhanin

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

Mikhail Hushchyn

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

À propos de National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communications, IT, mathematics, engineering, and more. Learn more on www.hse.ru...

À propos de la Spécialisation Advanced Machine Learning

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings....
Advanced Machine Learning

Foire Aux Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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