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自分のスケジュールですぐに学習を始めてください。

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上級レベル

約19時間で修了

推奨:5 weeks of study...

英語

字幕:英語, 韓国語

次における1の1コース

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

上級レベル

約19時間で修了

推奨:5 weeks of study...

英語

字幕:英語, 韓国語

シラバス - 本コースの学習内容

1
4時間で修了

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.

...
4件のビデオ (合計45分), 1 reading, 1 quiz
4件のビデオ
Experimental particle physics13 分
Testing hypotheses experimentally12 分
Particle physics simulation7 分
1件の学習用教材
Lecture slides10 分
2
5時間で修了

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.

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7件のビデオ (合計62分), 1 reading, 2 quizzes
7件のビデオ
Tracking system7 分
Ring Imaging Cherenkov detector6 分
Calorimeters11 分
Muon system8 分
Machine learning in particle identification6 分
Uniform classifiers12 分
1件の学習用教材
Lecture slides10 分
1の練習問題
Particle identification quiz20 分
3
7時間で修了

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.

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4件のビデオ (合計41分), 1 reading, 1 quiz
4件のビデオ
Lepton Flavour Violation14 分
Classifier Constraints12 分
Data vs Simulation Agreement5 分
1件の学習用教材
Lecture slides10 分
4
4時間で修了

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.

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5件のビデオ (合計41分), 1 reading, 1 quiz
5件のビデオ
Search for Dark Matter at Accelerator Experiment11 分
Getting Data Before Experiment is built10 分
Going Deeper9 分
Looking Ahead3 分
1件の学習用教材
Lecture slides10 分
4.4
5件のレビューChevron Right

Addressing Large Hadron Collider Challenges by Machine Learning からの人気レビュー

by WXOct 17th 2018

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

講師

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Andrei Ustyuzhanin

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

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

ロシア国立研究大学経済高等学院(National Research University Higher School of Economics)について

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 communicamathematics, engineering, and more. Learn more on www.hse.ru...

Advanced Machine Learningの専門講座について

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

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