Universitat Internacional de Catalunya
AI in Advertising II
Other languages of instruction: English, Spanish
Teaching staff
Introduction
The "Introduction to Artificial Intelligence" course offers a practical and multidisciplinary exploration of this field, aimed at students with no prior technical knowledge. With a focus on gaining a deep understanding of AI and the ability to communicate with experts, the course covers the history, opportunities, and challenges of AI, as well as its applications in digital transformation and data science. The transversal nature of this course makes it suitable for undergraduate students from any field of study. The course is designed to provide both the most innovative tools and a general understanding of the basic principles of AI, its concrete applications in various fields, and the ethical challenges it poses.
By the end of the academic program, participants will be equipped to anticipate the changes that AI technologies will bring to their environment, as well as understand how to react appropriately, capitalizing on these technologies for their benefit. The course will also address the regulatory and ethical challenges surrounding AI technologies, enabling participants to assess their relevance in the context of their respective fields.
Pre-course requirements
It is not necessary to have taken Applied AI in Advertising I.
Objectives
To train students in the use of Artificial Intelligence tools applied to the creation of advertising products and the implementation of multimedia advertising campaigns, with a focus on innovation, creativity, and interactive experiences.
Evaluation systems and criteria
In person
This course focuses on practical and innovative aspects of learning artificial intelligence. Therefore, knowledge will be acquired progressively.
Since assessment is continuous and based on assignments rather than a written exam, all submissions must be uploaded to the Moodle platform within the established deadlines for each task, in order to be counted as completed (some tasks must also be presented in class in front of classmates). Submissions cannot be sent by email, uploaded on behalf of another student (even for group work), or submitted after the deadline.
Assessment Breakdown:
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Individual practical tasks: 30%
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In-class exercises (group topic): 20%
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Final group project or portfolio and presentation. Teams of 2 people (maximum 3). The tools used must be explained, including the reasoning behind choosing those tools over others: 50%