MSc in Data science and economics (Università degli Studi di Milano)

The objective of the course is to introduce the fundamental concepts at the basis of massive data management and analysis, including the main processing techniques dealing with data at massive scale and their implementation on distributed computational frameworks.

Expected results

At the end of the module, students shall know the main approaches enabling them to analyze massive amounts of data, as well as the ability to design and execute computations on big data, deployed on modern distributed computing systems.


Date Info
21/02/2024 Tutoring «Algorithms for massive datasets» (DSE)
Students can attend five tutoring sessions, on February, 28th and on March, 6th, 13th, and 20th in classroom tau (città Studi) from 11:30 to 13:30.
20/02/2024 Projects for the «Algorithms for massive data» module (Master DSE)
The description of the projects for the module «Algorithms for massive data» for the Master in «Data Science for Economics» is available.


Lectures are in English.

Course schedule

Lectures take place at the Città Studi neighborhood according to the following schedule:

Day Hour Place
Tuesday 14:30 - 16:30 Aula 204
Wednesday 14:30 - 16:30 Aula 505

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

Written exam (prof. Anisetti, prof. Foresti)

Subscribe through UniMia to the exam call if you want to sustain one or both parts of the exam. You will receive an email a few days before the exam, asking you which part of the written part of the exam you will attend. If you already passed one of the two parts of the exam, please register through Ariel to be admitted to the written exam for the part you still need to sustain. Students who do not subscribe to the exam will not be admitted to sustain it. We need the exact number of people who will take the written exam, to suitably book classrooms.

Project and oral exam (prof. Malchiodi)

The exam of the Algorithms for massive datasets module 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 refer to the Web pages of the remaining modules for the description of the corresponding exam modalities.

You do not need to sign up through UniMia. Send an email to prof. Malchiodi within the project deadline (see table below), containing the link to your project. You will be contacted after the project has been checked. The table below shows a tentative date for the oral exams.

Final mark

Each module is passed if the corresponding mark is higher than or equal to 15/30. The overall exam is passed if the average mark (weighted w.r.t. the module credits) is higher than or equal to 18/30 and at most one of the three marks is below 18/30. The final mark will be recorded in association with your UniMia subscription for the written part of the exam.

Mark expiration

The mark of each part of the exam expires after 1 year. If, after one year from when you passed one of the parts of the exam, you did not register the final mark, you will need to repeat all the parts of the exam (also the ones you already passed).

Exam sessions

Session Date
April sign up date: 11/04, project deadline: 08/04, oral exams: 15/04
June sign up date: 17/06, project deadline: 12/06, oral exams: 19/06
July sign up date: 22/07, project deadline: 11/07, oral exams: 17/07
September sign up date: 10/09, project deadline: 13/09, oral exams: 18/09
November sign up date: 22/11, project deadline: 15/11, oral exams: 20/11
December sign up date: 12/12, project deadline: 09/12, oral exams: 13/12