In this class, we will explore the technologies that scholars use for humanities and social science research, delving into their history, advantages, and limitations. Additionally, we will examine the main ongoing discussions in the field of digital humanities.
The course is designed for participants with a diverse profile. It aims to provide the necessary skills for creating digital content to support research in political sciences, modern and contemporary history, economics, and textual sciences.
By the end of the course, you will have completed a digital humanities project for your personal portfolio. The project will be based on your research interests and will demonstrate the skills you have acquired. To achieve this, we will dedicate a portion of our weekly meetings to in-class exercitations and project discussions.
The course is designed for participants with a diverse profile. It aims to provide the necessary skills for creating digital content to support research in political sciences, modern and contemporary history, economics, and textual sciences.
By the end of the course, you will have completed a digital humanities project for your personal portfolio. The project will be based on your research interests and will demonstrate the skills you have acquired. To achieve this, we will dedicate a portion of our weekly meetings to in-class exercitations and project discussions.
scheda docente
materiale didattico
This year’s course will focus on the origins of Artificial Intelligence and its relevance to Digital Humanities.
Please refer to the course's website: https://digitalhumanities.site
- What is Digital Humanities? Can it be defined?
- What is ‘data’?
- Data cleaning and manipulation.
- Presenting data. Data analysis.
- Data visualization: history, methods, and tools.
- Text analysis and topic modeling; possibilities and drawbacks.
- Algorithms of textual analysis.
- Infographic: A history of data graphics.
- Introduction to AI: From the first models to machine learning.
- Deep machine learning.
- An introduction to artificial neural networks.
Programma
THE ORIGINS OF AIThis year’s course will focus on the origins of Artificial Intelligence and its relevance to Digital Humanities.
Please refer to the course's website: https://digitalhumanities.site
- What is Digital Humanities? Can it be defined?
- What is ‘data’?
- Data cleaning and manipulation.
- Presenting data. Data analysis.
- Data visualization: history, methods, and tools.
- Text analysis and topic modeling; possibilities and drawbacks.
- Algorithms of textual analysis.
- Infographic: A history of data graphics.
- Introduction to AI: From the first models to machine learning.
- Deep machine learning.
- An introduction to artificial neural networks.
Testi Adottati
The materials will be available on the course's website: https://digitalhumanities.siteBibliografia Di Riferimento
As for the bibliography, visit https://digitalhumanities.siteModalità Erogazione
The course is structured as a seminar. Each class typically consists of one or more of these elements: - Discussion of essays, articles, and projects that students have read before the lesson. During this phase, we will analyze the provided materials and explore some of the most relevant digital humanities projects in a reverse-engineering fashion. - Lecture. The lecture will primarily focus on the historical and methodological aspects related to the tools that will be used in the upcoming classes. - In-class exercise. Participants start getting familiar with the tools they will use for their final projects.Modalità Frequenza
- In general, regular class attendance is important, as part of the final evaluation is based on in-class activities. - For students enrolled in "International Studies", attendance is mandatory in accordance with course regulations.Modalità Valutazione
The evaluation consists of two parts: 1) Class Participation and Midterm Test: Students are expected to engage in weekly in-class discussions and take a written midterm test, administered during the second half of the course. This component accounts for 70% of the final grade. 2) Final Examination: On one of the official exam days, students will critically discuss their final project. This will make up the remaining 30% of the final grade.