95965 - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR BUSINESS

Anno Accademico 2024/2025

  • Docente: Giuseppe Magro
  • Crediti formativi: 6
  • SSD: ING-INF/05
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Bologna
  • Corso: Laurea Magistrale in Food Animal Metabolism and Management in the Circular Economy (cod. 5814)

Conoscenze e abilità da conseguire

At the end of the course the student is in possession of the basic knowledge of cutting-edge models and applications of artificial intelligence, with particular attention to machine learning. In particular, they are able to have a practical vision to select the appropriate methods to solve concrete problems

Contenuti

1 Decision Support Systems

- The concept of dynamic system and sustainability

- The structure of the decision-making process

- Classic and new generation decision support systems

- Operational techniques for implementing evidence based decision support systems

2 The Mathematical Models for Data Science

- Methods for developing mathematical models for business

- Classification and clustering regression algorithms

- Data Mining and automatic learning methods

- Operational data exploration tools for Business

3 Machine Learning

- Methodological and functional framework of learning systems

- Machine learning operational tools

- Analytical Platforms for Data Science from an ESG perspective

4 Applications of Machine Learning to concrete business cases

- Operational tools of E-governance for the Business

- Practical applications of ML for supervised learning predictions and recommendations

- Exercises of co-design of monitoring systems of ESG Business performances

Testi/Bibliografia

Course Materials

Metodi didattici

The teaching method used involves the integration of methodological contents with the operational aspects of real case studies of the application of Artificial Intelligence and focuses on inductive content coding techniques and the development of problem solving algorithms

Modalità di verifica e valutazione dell'apprendimento

At the end of the course there is a written test to verify the level of learning of the basic concepts and to evaluate the skills acquired in the application of the methods to concrete cases of application

Strumenti a supporto della didattica

KNIME software is used in the Course

Orario di ricevimento

Consulta il sito web di Giuseppe Magro