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</o:shapelayout></xml><![endif]--></head><body lang=IT link="#467886" vlink="#96607D" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNormal>Carissimi e carissime,<o:p></o:p></p><p class=MsoNormal>vi invio il link al modulo per potervi iscrivere al <b>Corso di Python</b> che si terrà nell’<b>Aula didattica </b>della <b>Residenza Biomedica</b> a partire dal prossimo <b>13 marzo (18-20).<o:p></o:p></b></p><p class=MsoNormal>Qui e nel form un breve programma e calendario del corso che avrà la durata di 20 ore. La docente di questo anno accademico sarà la <b>Prof.ssa Giovanna Nicora</b> Assistant professor (RTDa) presso il Laboratorio di Bioinformatica dell’Università di Pavia.<o:p></o:p></p><p class=MsoNormal>Il corso sarà ritenuto valido per le ore formative a fronte di una frequenza di almeno il 75% delle lezioni.<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><table class=MsoNormalTable border=1 cellspacing=0 cellpadding=0 width=600 style='border-collapse:collapse;border:none'><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal><b>Data<o:p></o:p></b></p></td><td width=499 valign=top style='width:374.25pt;border:solid black 1.0pt;border-left:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal><b>Argomento<o:p></o:p></b></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>13/03/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Introduzione al linguaggio Python: sintassi base, variabili e tipi di dati, strutture di controllo. Hands on: risolvere semplici esercizi in Python (ambiente Colab)*<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>20/03/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Python per il data mining e l’analisi dei dati: librerie numpy, pandas and matplotlib. Hands on: caricare un set di dati e calcolare semplici statistiche<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>27/03/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Introduzione all’Intelligenza Artificiale. Machine Learning supervisionato e non supervisionato<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>03/04/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Algoritmi di ML supervisionato: gli Alberi Decisionali. Hands on: implementare un albero decisionale in Python <o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>10/04/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Sviluppo e valutazione del modello: training e test. Introduzione al pacchetto Python sklearn per lo sviluppo di modelli di AI<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>17/04/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Valutazione delle performance di un classificatore. Metriche, matrice di confusione, cross validazione<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>22/05/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Regressione Logistica e Reti Neurali. Hands on: allenare e testare una rete neurale su un problema di interesse (es. predizione della prognosi di un paziente date le sue variabili cliniche)<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>29/05/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Overfitting, bias e varianza, generalizzazione di un modello di Machine Learning. Etica e safety. Hands on: esercizi sull’overfitting<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>05/06/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>Text Mining, Introduzione ai Large Language Model e ai Foundation Model<o:p></o:p></p></td></tr><tr><td width=101 valign=top style='width:75.75pt;border:solid black 1.0pt;border-top:none;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal>12/06/25<o:p></o:p></p></td><td width=499 valign=top style='width:374.25pt;border-top:none;border-left:none;border-bottom:solid black 1.0pt;border-right:solid black 1.0pt;padding:5.0pt 5.0pt 5.0pt 5.0pt'><p class=MsoNormal><span lang=EN-GB>Open Source Large Language Model con Python e HuggingFace. </span>Hands on: sviluppare un chatbot medico<o:p></o:p></p></td></tr></table><p class=MsoNormal><b><o:p> </o:p></b></p><p class=MsoNormal><b>*</b> gli hands on verranno effettuati usando l’ambiente Google Colab, disponibile su ogni tipo di browser. Gli studenti lavoreranno in gruppi di 2/3 usando un pc<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><b>Learning objectives<o:p></o:p></b></p><ul style='margin-top:0cm' type=disc><li class=MsoNormal style='mso-list:l0 level1 lfo1'>Comprendere le basi della programmazione in Python, con focus su applicazioni mediche.<o:p></o:p></li><li class=MsoNormal style='mso-list:l0 level1 lfo1'>Applicare tecniche di machine learning supervisionato su dataset reali.<o:p></o:p></li><li class=MsoNormal style='mso-list:l0 level1 lfo1'>Sperimentare l’uso di modelli di Intelligenza Artificiale generativa per applicazioni biomediche.<o:p></o:p></li><li class=MsoNormal style='mso-list:l0 level1 lfo1'>Sviluppare competenze pratiche nell'uso di librerie open-source come Scikit-learn, Pandas, e Hugging Face.<o:p></o:p></li></ul><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><a href="https://docs.google.com/forms/d/1KO1w22BflqRixC498emvZFG2OKN57k71vCqQw63lxz8/edit">https://docs.google.com/forms/d/1KO1w22BflqRixC498emvZFG2OKN57k71vCqQw63lxz8/edit</a><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>grazie e buona giornata<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>Eleonora<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span style='mso-ligatures:none;mso-fareast-language:IT'>Residenza Universitaria Biomedica<o:p></o:p></span></p><p class=MsoNormal><span style='mso-ligatures:none;mso-fareast-language:IT'>Fondazione Collegio Universitario S. Caterina da Siena<o:p></o:p></span></p><p class=MsoNormal><span style='mso-ligatures:none;mso-fareast-language:IT'>Via L. Giulotto, 12<o:p></o:p></span></p><p class=MsoNormal><span style='mso-ligatures:none;mso-fareast-language:IT'>27100 PAVIA – ITALIA<o:p></o:p></span></p><p class=MsoNormal><span style='mso-ligatures:none;mso-fareast-language:IT'>Dott.ssa Eleonora Ferrari<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='mso-ligatures:none;mso-fareast-language:IT'>tel: +39 0382 516762 - + 39 0382 516799<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='mso-ligatures:none;mso-fareast-language:IT'>email: </span><span style='mso-ligatures:none;mso-fareast-language:IT'><a href="mailto:biomedica.segreteria@collegiosantacaterina.it"><span lang=EN-US>biomedica.segreteria@collegiosantacaterina.it</span></a></span><span lang=EN-US style='mso-ligatures:none;mso-fareast-language:IT'><o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='mso-ligatures:none;mso-fareast-language:IT'>web: </span><span style='mso-ligatures:none;mso-fareast-language:IT'><a href="http://www.collegiosantacaterina.it/"><span lang=EN-US>http://www.collegiosantacaterina.it/</span></a></span><span style='mso-ligatures:none;mso-fareast-language:IT'> </span><span lang=EN-US style='mso-ligatures:none;mso-fareast-language:IT'><o:p></o:p></span></p><p class=MsoNormal><span lang=EN-GB><o:p> </o:p></span></p></div></body></html>