Study-unit DATA SCIENCE AND APPLICATIONS IN PHYSICS
Course name | Physics |
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Study-unit Code | A002331 |
Location | PERUGIA |
Curriculum | Astrofisica e astroparticelle |
Lecturer | Livio Fano' |
Lecturers |
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Hours |
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CFU | 6 |
Course Regulation | Coorte 2023 |
Supplied | 2023/24 |
Supplied other course regulation | |
Learning activities | Affine/integrativa |
Area | Attività formative affini o integrative |
Sector | FIS/04 |
Type of study-unit | Opzionale (Optional) |
Type of learning activities | Attività formativa monodisciplinare |
Language of instruction | Italian |
Contents | Introduction to statistical learning and to the most common tools |
Reference texts | The Elements of Statistical Learning (Data Mining, Inference, and Prediction) Autors: Trevor Hastie Robert Tibshirani Jerome Friedman |
Educational objectives | Learning from Data with statistical and computational tools for big and complex data. Specific applications to Physics. |
Prerequisites | "Statistical Methods for Data Analysis" is suggested. |
Teaching methods | Classroom lessons and practice. |
Other information | Data Science combines advanced statistical and computational methods, with specific infrastructural solutions at high scalability and high performances. |
Learning verification modality | Students will be requested to: 1) during the course: provide a presentation to the classroom based on one of the arguments discussed during the first half of the study program 2) end of the course: provide a written report on an assigned argument 3) oral test |
Extended program | Introduction to Statistical Learning: 1) Prediction accuracy, model preparation and supervised learning 2) Regression and Classification 3) Model selection 4) Decision Trees - random forest 5) Support Vector Machine 6) Unsupervised Learning and Principal Component Analysis 7) Neural Network and Deep Learning |