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72796 - Data Intensive Applications

Academic Year 2022/2023

                
                        Docente:
                        Gianluca Moro
                    
                        Credits:
                        6
                    
                        SSD:
                        ING-INF/05
                    
                        Language:
                        Italian
                    
                        Moduli:
                        
                            Gianluca Moro
                            (Modulo 1)
                        
                            Roberto Pasolini
                            (Modulo 2)
                        
                        Teaching Mode:
                        
                                    Traditional lectures (Modulo 1)
                                
                                    Traditional lectures (Modulo 2)
                                
                            Campus:
                            Cesena
                        
                            Corso:
                            First cycle degree programme (L) in
                            Computer Science and Engineering (cod. 8615)

                            Teaching resources on Virtuale
                        
                                        Course Timetable
                                    
from Feb 20, 2023 to Jun 05, 2023

                                        Course Timetable
                                    
from Feb 20, 2023 to Jun 05, 2023

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 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=37961)

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.

Assessment methods

Group work with individual oral discussion.

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 available with colab

Links to further information

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

Office hours

See the website of Gianluca Moro

See the website of Roberto Pasolini