HUMANITIES AND SOCIAL SCIENCES
Violence Against Women and Minors: understanding and contrasting the phenomenon.
Milano
Professional training
Italian
8 months
blended
Vision
Il Corso ha l’obiettivo di formare, grazie ad un approccio multidisciplinare, quelle figure professionali che a vario titolo si occupano della prevenzione e del contrasto della violenza contro donne e minori.
Mission
- Formare figure professionali per enti pubblici e privati che a vario titolo gestiscono le politiche di prevenzione e di contrasto o entrano in contatto con donne e minori vittime di violenza domestica;
- Specializzare risorse umane che operano in diversi campi culturali, aziendali, educativi nell’ambito della prevenzione e contrasto alla violenza;
- Rafforzare le competenze professionali di chi svolge attività lavorative in tema di prevenzione e contrasto della violenza di genere (come servizi socio-sanitari, servizi sociali e psicologici, centri antiviolenza, case rifugio, consulenti per politiche sociali);
- Contribuire alla formazione di futuri operatori/operatrici interessati al contrasto alla violenza di genere.
Structure
Il corso prevede le seguenti prove di valutazione:
- Due prove intermedie di autovalutazione scritte:
- Prima prova intermedia: verifica l’apprendimento relativo agli insegnamenti I-VI.
- Seconda prova intermedia: verifica l’apprendimento relativo agli insegnamenti VII-IX.
- Una prova finale.
Teaching Organization
120 hours of Lezione
Exams and Attendance
2
EXAMS
+
1
FINAL TEST
For a total of 20 CFU
REQUIRED
75 %
OF HOURS OF ATTENDANCE
Courses
- Definizioni e convenzioni internazionali.
- Convenzione di Istanbul.
- Problemi culturali e sociali.
- Violenza popolare e simbolica.
16 HOURS
2 CFU
- Prospettive intersezionali: genere, classe, etnia, disabilità, orientamento sessuale.
- Violenza nei confronti dei migranti.
8 HOURS
1 CFU
- Violenza contro i minori.
- Violenza assistita.
- Figlicidio e orfani.
- La tratta a scopo di sfruttamento sessuale.
16 HOURS
2 CFU
- Dove trovare i dati e come interpretarli.
- I dati relativi alle mutilazioni genitali femminili, matrimoni forzati: dove trovarli e come leggerli.
8 HOURS
2 CFU
- Le politiche pubbliche antiviolenza.
- Le azioni per la prevenzione e il contrasto delle MGF.
- Le azioni per la prevenzione e il contrasto delle molestie sui luoghi di lavoro.
8 HOURS
1 CFU
- La valutazione del rischio secondo il metodo SARA.
- La valutazione del rischio secondo il metodo DASH.
8 HOURS
1 CFU
- Come funziona un centro antiviolenza.
- Il ruolo del sistema socio-sanitario.
- I gruppi di mutuo-aiuto.
20 HOURS
3 CFU
- La violenza contro le donne come problema culturale e sociale.
- La socializzazione come prevenzione degli stereotipi.
- Il lavoro sull’identità maschile.
12 HOURS
1 CFU
- Violenza sulle donne e esperienza carceraria.
- La normativa italiana e la Corte europea dei diritti dell’uomo.
- La vittimizzazione secondaria.
- La donna nel processo penale e civile.
16 HOURS
1 CFU
Comitato scientifico
Direttrice
Componenti
What skills do you gain?
Il fenomeno e le sue caratteristiche
Sguardi intersezionali
Forme della violenza
Misurare la violenza
Azioni, politiche pubbliche e interventi integrati
Valutazione del rischio
Sostenere la donna con vissuti di violenza
Prevenire la violenza
Quali applicazioni del diritto?
Professional opportunities
Operatori e Operatrici
Formazione di figure professionali impiegate o impiegabili in abiti per la prevemzione e il contrasto della violenza di genere, con particolare riferimento alle politiche pubbliche:
- Enti pubblici e privati;
- Risorse umane in enti pubblici e privati;
- Servizi socio-sanitari, servizi sociali e psicologici, centri antiviolenza, case rifugio, consulenti per politiche sociali;
- Operatori e operatrici interessati al contrasto alla violenza di genere.
MEDICAL AND HEALTH
Methods and Data Analysis in Biomedical Research - MEDAL
Monza
Master 2 Level
English
12 months
blended
Vision
The Master in MEthods and DAta anaLysis in Biomedical research (MEDAL) is a unique study program that combines expertise in innovative study design with quantitative methods for data analysis in the field of Biomedical Research.
The training program of the Master aims at giving solid bases on the principles of study design and of appropriate methodologies for analysing data in preclinical, translational and clinical research in the context of precision medicine and clinical epidemiology.
The course will introduce concepts related to statistical methods and bioinformatics in a multidisciplinary approach that connects statistical models and exploratory methods typical of artificial intelligence.
As the field of health care continues its move toward precision medicine, new study designs, infrastructure and resources are needed to advance the effective use of biomedical data and information to improve human health. The master has a multidisciplinary approach combining statistical modelling, machine learning techniques, artificial intelligence, and bioinformatics tools.
The program offers an international classroom – a mix of students with diverse backgrounds, some beginning their career, others already having gained experience in the biomedical research.
Mission
With the fast development of new technologies, biomedical research has turned into a digitised and data-intensive science. To meet this, we need to develop and train the next generation of medical statisticians and researchers with quantitative skills who can design and implement research in the field of health science.
The need for advanced skills in data science continues to be high in both the public and private sectors, particularly in contexts that emphasise research in public health, clinical medicine, life sciences, biomedicine and biotechnology.
Training Objectives:
- To gain experience in the analysis and modelling of data from multiple sources in their application to biomedical research studies.
- To develop precision medicine research studies, including study design and study protocol development, target population, sample size definition, data analysis plan, data collection methods, data management and quality control approaches.
- Learn to implement classical statistical techniques, Bayesian and modern computational methods, and use scientific thinking in the interpretation of results.
- Know how to manage both classical studies (clinical trials) and clinical epidemiology and real-world studies also by integrating clinical big data or molecular biology and genetics in translational research.
- Collaborate and communicate effectively with researchers in related disciplines by developing the ability to work in multidisciplinary teams.
Structure
Teaching Organization
280 hours of Lezione
400 hours of Stage
Exams and Attendance
8
EXAMS
+
1
FINAL TEST
For a total of 60 CFU
REQUIRED
75 %
OF HOURS OF ATTENDANCE
Courses
- Welcome and introduction
- Taxonomy of the studies
- Descriptive statistics
- Introduction to R
- Probability, sensitivity, specificity and ROC curve
- Statistical Distribution Functions; Inference: hypothesis testing & confidence interval
- Variable transformation
32 HOURS
4 CFU
- Analysis of Variance (ANOVA)
- Principles of regression and models for continuous data
- Effect measures with binary endpoints
- Regression models for binary response
- Variable selection
- Prediction models
- Bayesian Analysis
- Missing data
32 HOURS
4 CFU
- R software
- Multiple testing
- Survival Analysis
40 HOURS
5 CFU
- Design of RCTs; Early phase study design; Biomarker based designs; Sample Size Calculation; Adaptive designs; Bayesian designs; Estimands; Study PASS (Post Authorization Safety Study) and PAES (Post Authorization Efficacy Study).
- Fundamental ethics principles in research; Data governance and regulatory landscape (GDPR); issues and models related to data access / data sharing; The Ethics and Law of Experiments on Animals; End of life issues and the rights of terminally ill patients; The role of Ethical Committees.
- Regulatory aspects & legislations: the view of AIFA; Regulatory aspects & legislations: the view of pharma; Regulatory aspects & legislations in the area of rare-diseases; Good clinical practices.
48 HOURS
6 CFU
- Epidemiological designs;
- Introduction to Real World Data;
- Geo-spatial analysis;
- Real World Data (Pharmaceutical);
- Introduction to causal models.
32 HOURS
4 CFU
- Protocol development;
- End Point;
- End point Surrogate;
- Organizing Data & Data Management, Case Report Form & ECRF;
- Safety issues;
- Safety data analysis;
- Analysis of longitudinal data;
- Practical Review (Def. of a protocol);
- Reporting results;
- Reproducibility;
- Meta-analysis
40 HOURS
5 CFU
- Introduction to machine learning;
- Unsupervised learning;
- Neural networks and deep learning;
- From data to models in pandemics;
- Interpretable and explainable artificial intelligence;
- Computational intelligence for biomedicine and healthcare;
- Bayesian and causal networks.
24 HOURS
3 CFU
- Basic principles of scientific writing
- How to write a scientific paper
- How to write a Review
- Case report
- Letter to the editor
- Authorship
- Cover letter
- Peer review and manuscript evaluation
- Communicating science
- Writing an effective abstract
- Poster and oral presentation
- Communicating science to general public
- Social Media Communication
16 HOURS
2 CFU
- Funding opportunities for Young Investigators in Italy and Europe;
- Understanding the review process: writing for success;
- How to develop an Irresistible idea;
- The writing schedule;
- Background and Review of Literature;
- Hypothesis, Aim of the study, Preliminary Results;
- Experimental design & methods;
- Time & deliverables;
- Pitfalls;
- Expected outcome;
- Dissemination;
- Future directions
16 HOURS
2 CFU
Scientific Committee
Director
Members
Domenico
Criuscolo
Criuscolo
Freelancer
What skills do you gain?
Quantitative Approach to Biomedical Research
Clinical Data Science: Advanced Statistics I
Clinical Data Science: Advanced Statistics II
Study Design
Biostatistics Epidemiological Real World Studies
Research in Practice
Research Grant Writing
Scientific Communication & Writing
Methods and Data Analysis in Biomedical Research - MEDAL
Who is it aimed at ?
The training provided in MEDAL is of relevance for clinical researchers in universities and hospitals who are involved in "non-profit" and "profit" trials that aim at optimising diagnosis and treatment approaches and also for personnel from CROs (Contract Research Organisations) and public and private research centres and companies involved in biomedical and translational studies.
Professional opportunities
Professionals
The MEDAL Master's in Biomedical Research contributes to the technical and scientific training of professionals with high expertise in designing and analyzing clinical databases using statistics, machine learning, and data mining tools.
Biomedical Researcher
The Master's program contributes to the advanced training of medical statisticians and researchers with quantitative skills, who work or wish to work in biomedical research, in private and public research institutions, universities, and CROs.