Titular Professors
The goals will focus on:
Understand the complexity of data analysis in basic science where big data volumes are managed.
Know the type of techniques used to solve the different challenges that appear in high energy physics, astrophysics, and medicine.
Apply the knowledge acquired previously in the master for solving a problem in HEP or exploring which challenges exist in other fields (biology, medicine, or others).
SYLLABUS
1. Introduction to High Energy Physics (HEP) experiments. Data volume and flow. Challenges implied. Real-time analysis.
2. Applications of Machine Learning techniques in HEP: data reconstruction, trigger, particle identification, etc.
3. Example in astrophysics (Gaia project).
4. Examples in other fields (as biology and medicine) through presentations done by students.
5. Presentation of a challenge similar to a Kaggle competition to be solved by the students.
Note: Topics can be adjusted and/or modified at the discretion of the master's coordination.
The methodology used combines master classes, student participation, practical exercise at class and solving a challenge or doing a research exercise as final work. For the student, this will involve individual (or group work), and an oral presentation at class.
This subject will be assessed on a continuous via the development of a challenge proposed or by a research work on already existing solutions in some scientific context and a final presentation in class.
Continuous assessment
This subject will be assessed on a continuous via the development of a challenge proposed or by a research work on already existing solutions in some scientific context and a final presentation in class.
The final grade will be a weighting of:
- Challenge solution (implementation) and/or presentation or research work: 80%
- Class participation: 20%
Extraordinary call
The exam and/or works of extraordinary call will be determined from the coordination of the subject.
Copies regulations
The subject is governed by the general regulations of copies of La Salle Campus BCN:
https://www.salleurl.edu/en/copies-regulation
The training activities will be considered to have the following category:
Final exercise or challenge: highly significant
The bibliography will be detailed throughout the course.
All class material (presentations, exercises, articles, documents, etc.) will be shared in the subject folder of the La Salle Intranet: eStudy.