Attendance

IMPORTANT - Due to the coronavirus emergency and the instructions issued by the competent authorities, traditional face-to-face lectures and lessons at Sapienza University have been suspended. However the M.Sc. in Data Science has activated online distance-learning resources since Monday, March 9th.  Currently, all courses are regularly taught online!! More  info available at the class schedule link. At the moment Sapienza University is managing to provide definite instructions for on-line course exams and online final graduation exam. Please follow the most recent updates on the Sapienza website.

 

More info: http://datascience.i3s.uniroma1.it/it

Orario delle lezioni

Choose your curriculum

First year (Year of enrolment 2019/2020)

Course Code Semester CFU SSD Language
ALGORITHMIC METHODS OF DATA MINING AND LABORATORY 1047221 First semester 9 ING-INF/05 English
FUNDAMENTALS OF DATA SCIENCE AND LABORATORY 1047264 First semester 9 INF/01 English
Statistical methods in data science and laboratory 10589600 First semester 9 English
Statistical methods in data science and laboratory 10589600 Second semester 3 English
INTELLECTUAL PROPERTY COMPETITION AND DATA PROTECTION LAW 1047215 Second semester 6 IUS/04 English
Economics of Network Industries 1047212 Second semester 6 SECS-P/06 English
NETWORKING FOR BIG DATA AND LABORATORY 1047223 Second semester 9 ING-INF/03 English
DATA MANAGEMENT FOR DATA SCIENCE 1047197 Second semester 6 ING-INF/05 English
CLOUD COMPUTING 1047205 Second semester 6 INF/01 English
DATA MINING TECHNOLOGY FOR BUSINESS AND SOCIETY 1047200 Second semester 6 ING-INF/05 English
STATISTICAL LEARNING 1047208 Second semester 6 SECS-S/01 English
QUANTITATIVE MODELS FOR ECONOMIC ANALYSIS AND MANAGEMENT 1047209 Second semester 6 ING-IND/35 English
A SCELTA DELLO STUDENTE Second semester 6 Italian

Second year (Year of enrolment 2018/2019)

Course Code Semester CFU SSD Language
DATA PRIVACY AND SECURITY 1047214 First semester 6 INF/01 English
SIGNAL PROCESSING FOR BIG DATA 1047202 First semester 6 ING-INF/03 English
Computational Data Analysis 10589623 First semester 6 ING-INF/05 English
OPTIMIZATION METHODS FOR MACHINE LEARNING 1041415 First semester 6 MAT/09 English
BIOINFORMATICS 1047220 First semester 6 ING-INF/06 English
Big Data for Official Statistics 1056085 First semester 6 SECS-S/05 English
DIGITAL EPIDEMIOLOGY 1047216 First semester 6 ING-INF/06 English
Neural Networks for Data Science Applications 10589627 First semester 6 ING-IND/31 English
A SCELTA DELLO STUDENTE First semester 6 Italian
EARTH OBSERVATION DATA ANALYSIS 1047218 Second semester 6 ING-INF/02 English
Data Driven Economics 1056129 Second semester 6 SECS-P/02 English
EFFICIENCY AND PRODUCTIVITY ANALYSIS 1047222 Second semester 6 SECS-S/03 English
Geomatics and Geoinformation 10589730 Second semester 6 ICAR/06 English
Smart Environments 1056023 Second semester 6 ING-INF/03 English
Advanced Machine Learning 10589621 Second semester 6 INF/01 English
STATISTICS FOR STOCHASTIC PROCESSES 1056087 Second semester 6 SECS-S/01 English
OTHER USEFUL SKILLS FOR INCLUSION IN THE WORLD OF WORK AAF1149 Second semester 3 Italian
Final exam AAF1022 Second semester 24 Italian

Schedule of exams - Academic Year 2018 - 2019:

http://datascience.i3s.uniroma1.it/it/node/5823

 

Teaching calendar:

https://web.uniroma1.it/i3s/en/node/9152

Highly qualified students who have enrolled to the second year of the M.Sc. in Data Science are eligible for the student honors program. Annual call is usually issued in December.
For the present academic year the official call for application is available here.
The submission deadline and the publication date of the results are specified in the call. Upon competitive criteria as detailed in the call (number of credits earned during the first academic year, weighted average grade), a limited number of students are selected and admitted to the Data Science student honors program. Selected students will be assigned to a tutor who will plan scientific and educational activities in addition to those being part of the regular course of study. These activities, for a maximum of 100 hours per year, may include participation to PhD seminars or to summer/winter schools, extra project work in the framework of a national or European research project or an internship with an industrial partner. In any case the activities must be assigned and approved by the tutor.

In order to successfully complete the honors program, students must conclude the additional planned scientific and educational activities in time and, by the end of their second year, the must earn all the credits prescribed for the regular course of study with a weighted average grade on exams larger or equal than twenty-seven (out of thirty). For those who enrolled as first-year students in a.y. 2018/2019 this means that they must be graduating by the end of January 2021.

Honors_programme_regulations_ita_vers_1.pdf

 

All information relating to the final exam is contained in the Graduation section