The course introduces students to the fundamental principles of Data Science, Business Analytics, and Artificial Intelligence, with a particular emphasis on leveraging data to support strategic decision-making in Digital Marketing and Digital Business.

Students become familiar with the complete data lifecycle, including data collection, preprocessing, analysis, visualization, and the development and evaluation of machine learning models for prediction, classification, and clustering tasks. Particular emphasis is placed on the application of contemporary Artificial Intelligence techniques to consumer behavior analysis, marketing optimization, and data-driven business decision-making.

The course presents a range of practical business analytics applications, including Customer Churn Prediction, Market Segmentation, Recommendation Systems, Customer Lifetime Value (CLV) prediction, Market Basket Analysis, Association Rule Mining, Conjoint Analysis, and Product Positioning strategies. It also introduces modern data visualization techniques, the development of interactive dashboards, and the use of Generative AI tools to support business data analysis, interpretation, and decision-making.

The course combines theoretical foundations with the analysis of real-world business cases and demonstrations of state-of-the-art AI platforms and analytics tools widely used in industry. Through examples drawn from digital marketing, e-commerce, and digital services, students develop the ability to transform raw data into actionable business insights and evidence-based strategic decisions.

Finally, the course examines the ethical, legal, and societal implications of data-driven decision-making, including data privacy and GDPR compliance, algorithmic transparency and explainability, fairness and bias in AI systems, and the responsible and trustworthy use of Artificial Intelligence in business environments.