Data Science for Economics and Health

Program Bilgisi

Seviye

Yüksek Lisans

Süre

2 yıl

Dil

İngilizce

Kampüs

Milan

Derece Sınıfı

LM-DATA - Data Science

Kabul Tipi

Open with entry requirements examination

Resmi Eğitim Dili

English

EU Deadline

EU candidates and equivalents: admission application from 22 January 2026 to 20 July 2026. Admitted students enrol from 5 May 2026 to 15 January 2027.

Non-EU Deadline

Non-EU candidates applying for a visa: admission application from 22 January 2026 to 30 April 2026. In addition, the admission notice requires pre-enrolment through Universitaly by 31 July 2026. Admitted students enrol from 5 May 2026 to 15 January 2027, and applicants with foreign qualifications must complete the enrolment documentation by 30 November 2026.

Akademik Koşullar

Applicants must hold a bachelor's degree or equivalent university qualification, or graduate by 31 December 2026. The manifesto states 180 credits are required for admission. Candidates must have earned at least 30 ECTS in one or more of the following areas: computer science and mathematics (MAT-01 to MAT-09, INF-01, INGINF/05), economic sciences and statistics (SECS-S/01, SECS-S/02, SECS-S/03, SECS-S/06, SECS-P/05, SECS-P/01, SECS-P/02, SECS-P/03, SECS-P/07, SECS-P/08, SECS-P/10), and/or medical sciences (MED/01 only). Curricular requirements must be met by the date of effective submission of the admission application. Candidates with foreign qualifications may be admitted if the qualification is recognized as appropriate by the University under the applicable ministerial rules and bilateral agreements. Admission is not automatic after credit checking: after the written admission test, the Admission Board evaluates the applicant's academic curriculum, including the quality of the previous degree, average grade, grades in mathematics/statistics/computer science/economics, and the coherence of prior studies or activities with the learning objectives of the programme.

Dil Koşulları

English proficiency at CEFR B2 or higher is required for admission. UniMi states that the requirement can be satisfied by: 1) a valid accepted English certificate at B2 or higher, issued no more than 3 years before the application date and uploaded during the admission procedure; 2) an English level certified by UniMi SLAM during a previous UniMi degree, provided it was achieved no more than 4 years before the application date, with automatic verification; or 3) the SLAM English entry test. If the applicant does not upload a valid certificate or the prior SLAM certification is expired/not valid, the applicant must take the SLAM entry test according to the official calendar. If the applicant fails or misses the SLAM test without an accepted excuse, they must submit an accepted language certificate via InformaStudenti under the 'language test' category by 31 December 2026 for DSEH. The DSEH application page also states that applicants who fail to meet the English requirement by the programme deadline will not be admitted.

Sınav / Test

DSEH uses a written online admission test in English to assess personal competencies and skills. According to the DSEH application page, the background knowledge test consists of 40 multiple-choice questions in 60 minutes: 10 Economics, 10 Statistics, 10 Mathematics, and 10 Computer Science. The passing threshold is 40%, with at least 16 correct answers overall, including at least 8 correct in Economics/Statistics and at least 8 correct in Mathematics/Computer Science. For A.Y. 2026/2027 the published test dates are 17 April 2026 for those who applied by March 2026, 15 May 2026 for those who applied by April 2026, 19 June 2026 for those who applied by May 2026, and 3 August 2026 for those who applied by June/July 2026. Candidates can take the background test only once, in the session to which they are invited. After the written test, the Admission Board may also request an online oral technical interview. The official DSEH interview-topics PDF lists mathematics/statistics topics such as derivatives, matrices, probability, estimation, confidence intervals, and hypothesis testing; computer science topics such as introductory programming, algorithms, data structures, databases, SQL, and computer networks; and economics topics such as microeconomics, macroeconomics, demand, costs, revenues, market equilibrium, GDP, growth, saving, investment, unemployment, and money/banking.