Instructor & Schedule

Claire David, PhD

 
 

I am an experimental particle physicist, and as such I study the Universe through its tiniest, most fundamental constituents: the elementary particles. I am involved in two international collaborations: the ATLAS Experiment, which is one of the detectors of the Large Hadron Collider (LHC) at CERN, and the Deep Underground Neutrino Experiment (DUNE), which is a future detector to be hosted by the US laboratory Fermilab near Chicago, Illinois.

I was initially trained as an engineer at the Institut National des Sciences Appliquées (INSA) in Toulouse, France.

I switched to fundamental science with a PhD in Particle Physics at the University of Victoria in Canada. I was based at TRIUMF in Vancouver and was stationned from 2012 until mid-2013 at CERN between Switzerland and France.

After a postdoctoral fellowship at DESY in Hamburg, Germany, I started as Assistant Professor at York University, north of Toronto, Canada.

More information on my webpage.

Schedule

By weeks

The table below shows a tentative weekly schedule for this course. There may be adjustements and as you can see there is time dedicated for reviews. The tutorials will run mostly during evening sessions so that you can learn at your own pace.

 
 

Incoming

A mini-version of this course is likely to be held in March/April 2023. If you want to know more, contact me.

Previous versions

\(\checkmark\) AIMS South Africa, February 2023
\(\checkmark\) AIMS Senegal, January 2023
\(\checkmark\) Partial course (Lectures 1 - 3) at the African School of Physics (ASP2022) in Gqebera, South Africa on December 9, 2022.

Acknowledgments

I have received the precious help of colleagues and friends. A big thank you to Harrison Prosper for being a great mentor and sharing valuable resources. I would also like to thank Alex Held, Benjamin Nachman, Bruno Barton-Singer, Clara Nellist, Dag Gillberg, Matthew Feickert, Sascha Caron and Will Leight.

For this course I got inspired by Coursera’s Introduction to Machine Learning, by Andrew Ng. I found wonderful tutorials in Machine Learning Mastery, by Dr. Jason Brownlee. Aurélien Géron’s book Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow (Second Edition) is fabulous. I am grateful to all ‘StackOverflowers’ helping me debug some parts of code to shape the tutorials and assignments into, I hope, an awesome learning experience for the students.