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72796 - Data Intensive Applications

Academic Year 2024/2025

                
                        Docente:
                        Gianluca Moro
                    
                        Credits:
                        6
                    
                        SSD:
                        ING-INF/05
                    
                        Language:
                        Italian
                    
                        Teaching Mode:
                        Traditional lectures
                        
                            Campus:
                            Cesena
                        
                            Corso:
                            First cycle degree programme (L) in
                            Computer Science and Engineering (cod. 8615)

                            Online Lessons
                        
                            Teaching resources on Virtuale

Learning outcomes

At the end of the course the student is able to design and develop intelligent applications of corporate interest by processing structured and unsctructured data with modern data science methods and fundamental machine learning technologies.

Course contents

The course covers the fundamentals of data science and machine learning from basic algorithms to neural networks for developing AI applications in python.

Course Content Details

https://bit.ly/3aG9Brb

Lectures and Laboratories

course web site (https://virtuale.unibo.it/course/view.php?id=52948)

The material view does not require the enrolment to the course (in this case access the course web site selecting "spontaneous registration")

Readings/Bibliography

Materials and bibliographic references supplied by the teacher

Suggested course book

Data Science from Scratch, Joel Grus, O’Reilly Media, 2019 early edition freely available (previous edition 2015). Italian edition 2021, Data Science con Python. Dai Fondamenti al Machine Learning. Scientific Editor Gianluca Moro. Published by EGEA.

Teaching methods

Lectures are followed by aided laboratory practicals on real case studies of machine learning and data science for the development of artificial intelligence applications in several industrial and social domains.

Assessment methods

Group project work with individual oral discussion of the project. Students can choose the AI theme of the project.

Teaching tools

slides of lectures and laboratory practicals available in advance
python and jupyter open source technologies fully available in the school laboratories
aided laboratory activities linked also to open cloud computing such as colab or binder to perform them online remotely
example of a laboratory practical in python available with google colab

Link to the lessons of 2022/23. The contents of machine learning for the 2023/24 will be updated according to the most recent solution of the academic and industrial communities of AI:

https://virtuale.unibo.it/course/view.php?id=37961

Office hours

See the website of Gianluca Moro

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.