4 CFU

Machine Learning Methods For Physics – 6 CFU (optD)

Simona Ranieri 2nd year, 4 CFU, a.a. 2026-27, Block D-Computational Methods, II semester, optD, Subjects
Machine Learning Methods For Physics – 6 CFU (optD)

block optD – COMPUTATIONAL METHODS
2nd Year II semester
Course Information
Course Code 80300140
Credits 6 CFU
Offered by https://www.master-mass.eu/ (from Physics LM-17 )
SSD2015 FIS/01
SSD2024 PHYS-01/A
note
  • PREREQUISITES: Basic concepts of Linear Algebra, Mathematical Analysis and Python Programming

 

Lecturer
Current Lecturer
Prof.  Michele BUZZICOTTI
✉ Michele.Buzzicotti@roma2.infn.it
☏ +39-06-7259-4584
Previous Lecturer
✉

 

 

 

 

 

 

 

Grading Criteria
Evaluation Oral exam

 

Resources
Links

https://t0.gstatic.com/faviconV2?client=SOCIAL&type=FAVICON&fallback_opts=TYPE,SIZE,URL&url=https://didatticaweb.uniroma2.it&size=32  DidatticaWeb
ℹ️ Official Course Information (GOMP)

📑 Course Syllabus (details):  PHY – Machine Learning Methods for Physics (MLMP) — M. Buzzicotti

 

Laboratory Calculus – 4 CFU (block D)

Simona Ranieri 2nd year, 4 CFU, a.a. 2026-27, Block D-Computational Methods, I sem, Subjects
Laboratory Calculus – 4 CFU (block D)

block D – COMPUTATIONAL METHODS
2nd Year I semester
Course Information
Course Code 8068589
Credits 4 CFU
Offered by Pure and Applied Mathematics
SSD2015
SSD2024 INFO-01/A
note

 

Lecturer
Current Lecturer
Prof. Hendrik Speleers
✉
☏ 06. 7259.4634
Previous Lecturer
✉

 

 

 

 

 

 

 

Grading Criteria
Evaluation Oral exam and project evaluation

 

Resources
Links

https://t0.gstatic.com/faviconV2?client=SOCIAL&type=FAVICON&fallback_opts=TYPE,SIZE,URL&url=https://didatticaweb.uniroma2.it&size=32  DidatticaWeb
ℹ️ Official Course Information (GOMP)

📑 Course Syllabus (details):  MAT – Laboratory-Calculus (LC) — Speleers