MSc in Computer science (Università degli Studi di Milano)

The course aims at describing the big data processing framework, both in terms of methodologies and technologies.

Expected results



Date Info
09/06/2023 Joint project for the «Algorithms for massive datasets» and «Statistical methods for machine learning» courses (Master in Computer Science)
The description of a joint project for the courses «Algorithms for massive datasets» and «Statistical methods for machine learrning» for the Master in «Computer Science» is available.
14/06/2023 Office hours on June, 15th
The office hours of June, 15th are canceled.
07/06/2023 Office hours on June, 8th
The office hours of June, 8th will take place remotely, using the address
16/05/2023 Projects for the «Algorithms for massive datasets» course (Master in Computer Science)
The description of the projects for the course «Algorithms for massive datasets» for the Master in «Computer Science» are available. A joint project with the «Statistical methods for machine learning» course will be published shortly.
22/03/2023 Classroom change for the lectures
Starting March 28th, he lectures of the course «Algorithms for massive datasets» will take place in the classrooms V8 (on Tuesday) and 304 (on Wednesday), from 14:30 till 16:30.
16/03/2023 Office hours on March, 23rd
The office hours of March, 23rd are canceled.


Lectures are in English.

Course schedule

Lectures take place in presence, during the spring semester, at the "Città studi" educational sector. The schedule is as follows:

Day Hour Place
Tuesday 14:30 - 16:30 110 V8
Wednesday 14:30 - 16:30 110 304

Any change to the schedule will be announced in class and published in paragraph News of this page.

Office hours

By appointment, room 5015 of the Computer Science Department. It is possible contact the teacher by e-mail, taking care to read in advance the guide prepared by Prof. Sebastiano Vigna and clearly specifying in the message the course name and the academic year. In particular, students are encouraged to always use their academic address (i.e. based on the domain signing with name and student ID number and recalling that the response time may vary depending on the teacher commitments.

Course material

Lectures are based:


The course explains the topics listed in the lecture calendar (available at the beginning of the course), covering the textbook contents as well as the contents of the remaining documents listed in Course material.


The course requires knowledge of the main topics of bachelor-level computer programming, calculus, probability, and statistics.

Lectures calendar


Exam modalities

The exam consists of a project and an oral test, both related to the topics covered in the course. The project requires to process one or more datasets through the critical application of the techniques described during the classes, and is described in a written report.

The evaluation of the project, expressed with a pass/fail mark, considers the level of mastery of the topics and the clarity of the report. The oral test, which is accessed after a positive evaluation of the project, is based on the discussion of some topics covered in the course and on in-depth questions about the presented project. The evaluation of the oral test, expressed on a scale between 0 and 30, takes into account the level of mastery of the topics, clarity, and language skills.

Students should sign up at the chosen examination session through UniMia, and send en email to prof. Malchiodi within the project deadline (see table below), containing the link to the project. Students will be contacted after the project has been checked. The table below shows a tentative date for the oral exams.

Exam sessions

Session Date
June 16/06/2023 (project deadline: 12/06)
July 07/07/2023 (project deadline: 03/07)
September 15/09/2023 (project deadline: 11/09)
January 22/01/2024 (project deadline: 17/01)
February 06/02/2024 (project deadline: 31/01)
February 21/02/2024 (project deadline: 14/02)