Basic Recommender Systems

Politecnico di Milano in Milan is Italy's premier technical university, founded in 1863 and renowned for excellence in engineering, architecture, and design. With multiple campuses across Lombardy, the university attracts a global student body and emphasizes innovation, high-quality research, and strong industry collaboration. Its reputation for technical rigor and creative problem solving makes it a top choice for students aiming for leadership in technology and design fields.

The university offers bachelor, master and doctoral programs, many taught in English, covering engineering disciplines, architecture, industrial design and emerging technologies. Partnerships with leading companies and active participation in European research initiatives provide students with opportunities for internships, collaborative projects and access to innovation ecosystems. Facilities and innovation hubs support entrepreneurship and technology transfer.

Politecnico di Milano prioritizes employability through industry-linked curricula, career services and startup incubators. Students benefit from a vibrant urban setting in Milan, strong alumni networks and international exchanges that enhance career prospects worldwide. For students seeking rigorous technical training combined with creativity, entrepreneurship and real-world application, Politecnico di Milano offers an inspiring, professionally focused environment.

Basic Recommender Systems is a non-degree program for students of all levels, taught in English and lasting several weeks, offered online by Politecnico di Milano, introducing students to the fundamentals of recommender systems.

The curriculum includes subjects like data filtering, collaborative filtering, and content-based filtering, with students developing skills in data analysis, machine learning, and programming, and gaining hands-on experience with recommender system tools and technologies.

Graduates can pursue careers as Data Scientists, Recommendation Engine Developers, or Personalization Engineers, working for companies like Netflix, Amazon, or Spotify, in industries such as e-commerce, entertainment, or advertising.