Obiettivi formativi
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.
Prerequisiti
Working knowledge of basic statistics and marketing principles.
Risultati di apprendimento attesi
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.
Contenuti Del Corso
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.
Testi Di Riferimento
All the class material is available on the e-learning platform (slides, lecture notes, and reference to the textbook).
Metodologie Didattiche
The following teaching methods will be used during the course: - Traditional Lecture - Lab
Modalità di verifica dell'apprendimento
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).
Criteri per l’assegnazione dell’elaborato finale
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.
Settimana 1
Introduction to the course.
Settimana 2
Introduction to Artificial Intelligence.
Settimana 3
Introduction to web pages, server client architecture, static and dynamic websites, domain names and DNS.
Lab: Introduction to online marketing tools
Settimana 4
Cryptocurrencies, Blockchains, Smart Contracts and NFTs.
Lab: Introduction to the workgroup: running at least two weeks of a Google Ads campaign with, possibly, a real customer.
Settimana 5
Introduction to Machine Learning.
Lab: Google Ads certifications part 1.
Settimana 6
Machine Learning techniques part I: supervised learning.
Lab: Google Ads certifications, part 2.
Settimana 7
Machine Learning techniques part II: unsupervised learning.
Lab: running a Google Ads campaign.
Settimana 8
Machine Learning techniques part III: Artificial Neural Networks.
Lab: Google Analytics.
Settimana 9
Artificial Intelligence: history and current trends.
Lab: workgroup campaign reports (pre campaign).
Settimana 10
Introduction to the Internet of Things (IoT). IoT devices and application areas.
Lab: workgroup campaign reports (campaigns running).
Settimana 11
Artificial Intelligence for Marketing.
Lab: workgroup campaign reports (post campaign).
Settimana 12
Course recap.
Lab: workgroup campaign reports (post campaign).