Algorithms for Massive Datasets

A.Y. 2024/2025
6
Max ECTS
48
Overall hours
SSD
INF/01
Language
English
Learning objectives
The course aims at describing the big data processing framework, both in terms of methodologies and technologies.
Expected learning outcomes
Students:
- will be able to use technologies for the distributed storage of datasets;
- will know the map-reduce distributed processing framework and its leading extensions;
- will know the principal algorithms used in order to deal with classical big data problems, as well as to implement them using a distributed processing framework;
- will be able to choose appropriate methods for solving big data problems.
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor: Malchiodi Dario
Shifts:
Turno
Professor: Malchiodi Dario
Professor(s)
Reception:
By appointment
Room 5015 of the Computer Science Department