The course provides the basis for understanding Artificial Intelligence Applications to Marketing. In particular, the course will first provide an overview of general machine learning tools and techniques, and then it will focus on machine learning based tools for online marketing, such as Google Ads.

At the end of the course the student will understand the main ideas and techniques used in machine learning and artificial intelligence. In addition, he will be able to run an online marketing campaign using Google Ads. Also, through a group project activity, the student will learn how to clearly communicate the results of the online Google Ads campaign project.

The syllabus consists of a theoretical part and a practical part. The contents of both parts are described below. The theoretical part include an overview of artificial intelligence and machine learning areas like supervised and unsupervised learning, and also tools and techniques for specific problems such as classification, clustering and collaborative filtering. Machine learning based tools for online marketing: Google Adwords and Facebook Ads. Basic principles of the Internet Of things: devices and application areas. Marketing devices and marketing through devices. The practical part includes running a Google Ads campaign.

All the class material is available on the e-learning platform (slides, lecture notes, and reference to the textbook).

The following teaching methods will be used during the course: - Traditional Lecture - Lab

The competences are assessed via a written exam only. There is an intermediate (written) test concerning the theoretical part, that accounts for approximately one quarter of the final grade (i.e., the theoretical part is one half of the final grade, and the workgroup activities the other half).

The final work will be assigned (upon specific request to the instructor) to all students who demonstrate a serious and motivated interest to study the topics addressed in the course.