Esta página web está dedicada a la docencia de los títulos propios.

Puedes Obtener información de matrícula en la página web del Servicio de Titulaciones Propias

This applied, tools-oriented course introduces Artificial Intelligence (AI) as a broad field, positioning contemporary methods within their historical and societal context while emphasising practical understanding over formal mathematics. Students examine AI as systems that optimise decisions from data, progressing from foundational concepts and data analytics to machine learning (supervised/unsupervised/reinforcement), deep learning, and large language models (LLMs). The course highlights the capabilities of generative AI, AI agents, and automation, as well as an end-to-end workflow from data collection to deployment, utilising Python/MATLAB/cloud, and no-code platforms. Ethical, legal and societal implications – privacy, bias, transparency, safety, and regulation – are integrated throughout. By the end, participants can recognise appropriate AI use cases, interpret model behaviour and limitations, and select suitable tools to prototype AI solutions responsibly.

https://www.uptech-project.eu/artificial-intelligence-synchronous/

  • Profesor: Brlecic Valcic Sonja
  • Profesor: Cavallin Elena
  • Profesor: Cocca Vanessa
  • Profesor: Kalloniatis Christos
  • Profesor: Kolarić Alica
  • Profesor: López Muñoz Francisco Javier
  • Profesor: Opačak Eror Marija
  • Profesor: Panjkota Ante
  • Profesor: Perkov Josipa
  • Profesor: Román Castro Rodrigo
  • Profesor: Sarlija Marko
  • Profesor: Scarpa Massimiliano
  • Profesor: Tomasovic Zeljka
  • Profesor: Valcic Marko
  • Profesor: Zamparo Stefano