Generative Artificial Intelligence: Labs & Toolkits

The Generative Artificial Intelligence: Lab & Toolkits course provides a comprehensive overview of Generative Artificial Intelligence systems and their creative potential within the field of Artificial Intelligence. Generative Artificial Intelligence (Generative AI) is a rapidly evolving field that focuses on developing algorithms and models capable of autonomously generating creative content, such as images, text, music, and much more.

Throughout the course, students will be introduced to the key theoretical concepts and practical methodologies of Generative Artificial Intelligence. Starting with the basics of Machine Learning (ML), they will delve into the main architectures used for content generation, including Generative Adversarial Networks (GANs) and encoder-decoder models. The most popular tools and software libraries in the field of Generative AI will also be introduced.

The course will also delve into the main challenges and ethical implications of using Generative Artificial Intelligence.

Course content

• Week 1: Introduction to the course and the fundamental concepts of Artificial Intelligence and Machine Learning 
• Week 2: Fundamentals of Machine Learning 
• Week 3: Generative Artificial Intelligence – Part 1 
• Week 4: Generative Artificial Intelligence – Part 2 
• Week 5: Introduction to Prompt Engineering 
• Week 6: Advanced Prompt Engineering 
• Week 7: Generative AI models and ethical considerations 
• Week 8: Agentic AI 
• Week 9: Course conclusion and presentation of the Project Work 
• Week 10: Course conclusion and presentation of the Project Work 

Throughout the course, students will have the chance to put their newly acquired knowledge into practice through a series of applied exercises and the completion of a final group project.

By the end of the course, students will understand the theoretical foundations of Artificial Intelligence and be able to use practical tools to explore its creative potential. The course is aimed at both aspiring developers and those looking to integrate Generative AI into their professional or creative field, offering new opportunities for innovation and expression.

The lessons will alternate between lectures and practical, hands-on activities. The first four lessons will focus on building a theoretical foundation in Machine Learning and Artificial Intelligence, with a particular emphasis on Generative AI. The subsequent sessions will be entirely focused on practical activities, while the final part of the course will be dedicated to the presentation of the project work completed by the students.

Lecturers

Alessio Martino – Giorgio Piccardo

General Rules

• The course has a total duration of 30 hours, after which students will be required to work on the assigned project work. To have the University Credits recognised, you must have attended 80% of the total hours, which amounts to 24 hours (so you can be absent for a maximum of 6 hours), and the lecturer must deem you eligible for the final assessment.
• A tutor will be responsible for recording attendance, which will be done by signing a register. Failure to sign in and/or out will be considered an absence. There will be no exceptions to the sole criterion for awarding university credits: attendance.
• Absence hours will be calculated based on the attendance records. Depending on the schedule or personal needs, students can either take a full day off or miss individual hours across multiple lessons.
• Once a student has chosen their pathway, they will not be able to earn University Credits through any other means.
• Students who have already earned the University Credits required by their study plan for Other Activities, or who have already started attending optional language courses or other activities for which credits are recognised, are excluded.

Additional information

• The course will take place during the first semester.
• The course will be delivered in English.
• All sessions will take place on either a Friday or a Saturday.

The activity schedule will be available in September.

Registration

Students enrolled in the second year of the Bachelor’s Degree programmes in Economics and Management, Management and Artificial Intelligence, Business Administration, Economics and Business, Political Science, and Global Law for the 2026/2027 academic year, as well as those enrolled in the third year of the Single-Cycle Master’s Degree in Law for the 2026/2027 academic year, will be able to select the Soft Skills Generative Artificial Intelligence: Lab & Toolkits course directly via Web Self Service while completing their Study Plan, in order to earn the relevant credits.

For more information, please email: softskills@luiss.it