2. Teaching
  3. International Teaching
  4. Single courses (exams) taught in english language

MARKETING & ARTIFICIAL INTELLIGENCE LAB

International Teaching MARKETING & ARTIFICIAL INTELLIGENCE LAB

Back

0323200022
DEPARTMENT OF POLITICAL AND COMMUNICATION SCIENCES
EQF7
DIGITAL MARKETING
2025/2026

OBBLIGATORIO
YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2024
SPRING SEMESTER
CFUHOURSACTIVITY
945LAB
MARA GRIMALDI T Curriculum
Objectives
The Marketing & Artificial Intelligence Lab course will allow students to learn about the opportunities arising from the integration of marketing and artificial intelligence. During the lessons, combining theoretical and practical aspects, the advantages deriving from the integration of predictive analysis techniques with the personalization of content and the automation of marketing functions through Artificial Intelligence (AI) applications will be highlighted.

KNOWLEDGE AND ABILITY TO UNDERSTAND
During the course, students will understand predictive analytical models applied to marketing, using tools suitable for content personalization strategies and automation of marketing functions, through solutions based on Artificial Intelligence.

INDEPENDENCE OF JUDGMENT
The course will promote students' ability to evaluate the effectiveness of AI-powered marketing tools as well as the ability to evaluate the ethics of the multiple strategic alternatives made available by AI applications.

COMMUNICATION SKILLS
The course will allow students to train their communication skills through presentations and group discussions, as well as collaborative skills for the realization of projects that require an effective exchange of ideas, adequate skills and a predisposition to work in a team.

LEARNING ABILITY
The Marketing & Artificial Intelligence Lab aims to enable learners to develop flexibility in autonomous learning and in adapting to new trends and emerging technologies in the field of digital marketing and AI.
Prerequisites
A basic knowledge of digital marketing and familiarity with the concepts of Artificial Intelligence is required.
Contents
-Introduction to Artificial Intelligence (AI) in Marketing (4h)
-Predictive Analytics and Analytical Models in Marketing (4h)
-Content Personalization and Recommendation Algorithms (4h)
-Chatbots and Virtual Assistance (4h)
-Search Engine Optimization (SEO) with AI (4h)
-Advanced AI-Powered Marketing Automation (4h)
-Big Data Analytics in Marketing (8h)
-Automated Content Generation and Ethics in AI (8h)
Teaching Methods
The course is divided into interactive lessons (20 hours), case studies and real-world scenario analysis (4h), project work to apply the knowledge acquired (10h) and discussion of them (6h).
The interactive lessons aim to offer a complete vision of the combination of marketing and artificial intelligence. Through an approach that combines theory, strategy and practical tools, the interactive sessions will offer students the opportunity to actively participate, ask questions and discuss the concrete applications of the concepts covered.
Through the real-world scenario analysis, students will be able to directly apply the knowledge acquired. The project works will constitute a crucial element for developing problem solving skills, collaboration and the application of digital marketing strategies supported by artificial intelligence. Finally, the discussion of the projects will help students develop public speaking skills.
Verification of learning
The exam can be taken on the exam dates scheduled in the calendar and consists of a test aimed at verifying the knowledge learned and the carrying out of a project work.
The final grade, expressed in thirtieths with possible honours, will depend on the overall maturity acquired on the contents of the course.
The following will be taken into account:
-the quality of the presentation, in terms of the use of appropriate scientific language;
-the ability to cross-correlate between the different topics of the course and, where possible, with other disciplines;
-demonstrated autonomy of judgement.
The overall evaluation is normally obtained as the average of the oral exam and presentation of the project work.
Texts
Di Fraia G., Fare marketing con l'AI: Intelligenza (Artificiale) Aumentata per comunicare brand, prodotti e idee, HOEPLI EDITORE, 2020.
More Information
Recommended Reading:
Mandelli A., Intelligenza artificiale e marketing: Agenti invisibili, esperienza, valore e business, EGEA spa, 2018.
Leventhal B., Predictive Analytics for Marketers: Using Data Mining for Business Advantage, Kogan Page Publishers, 2018.
During the course, handouts and teaching material will be made available
  BETA VERSION Data source ESSE3