Statistical Data Analysis and Machine Learning for Neutrino Physics - Lecture 1
International Centre for Theoretical Sciences via YouTube
MIT Sloan AI Adoption: Build a Playbook That Drives Real Business ROI
Stuck in Tutorial Hell? Learn Backend Dev the Right Way
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore the fundamentals of statistical data analysis and machine learning in neutrino physics through this lecture by Adam Aurisano. Part of the "Understanding the Universe Through Neutrinos" program at the International Centre for Theoretical Sciences, this talk introduces key concepts and techniques used in analyzing complex neutrino data. Learn how statistical methods and machine learning algorithms are applied to extract meaningful insights from neutrino experiments, addressing critical questions in particle physics beyond the Standard Model. Gain valuable knowledge on data processing, statistical inference, and machine learning applications specific to neutrino research, setting the foundation for advanced studies in this cutting-edge field of physics.
Syllabus
Statistical Data Analysis and ML- (Lecture 1) by Adam Aurisano
Taught by
International Centre for Theoretical Sciences