Study plan for the cohort starting in a.y. 2024/25

• Analysis A or B (9)
• Probability theory (9)
• Statistical Inference (9)
• One course chosen between:
  • R Programming for Data Science (3)
  • Python Programming for Data Science (3)

• Stochastic Processes (6)
• One course chosen between (*):
• Statistics for Stochastic Processes (6)
• Stochastic Modelling for Statistical Applications (6) [not offered in 2024/25 and 2025/26]
• Multivariate Statistical Analysis (6)
• Databases and Algorithms (12)

(*) Students can take both courses in this rule without using free credits by choosing the first in the above rule and the second in the rule below. Both courses can be taken from the first year.

• Partial and Stochastic Differential Equations (6)
• Three courses chosen as follows (**):
• At least one course chosen among:
  • Bayesian Statistics (6)
  • Introduction to Data Mining (6)
  • Statistical Machine Learning (6) (2^nd semester in a.y. 2024/25)
• Remaining courses (if any) chosen among:
  
  • Applied Stochastic Calculus (6)
  • Complex Networks (6)
  • Computational Methods for Statistics (6)
  • Decisions and Uncertainty (6)
  • Deep Learning (6)
  • Econometrics (6)
  • Game Theory (6)
    
  • Information Theory (6)
  • Simulation (6)
    
  • Simulation Models for Economics (6)
• Freely chosen credits (12)
  
• Thesis (24)

(**) Courses in this rule offered at the second semester can be anticipated to the first year, in particular Statistical Machine Learning. The 3 courses in the first subrule are core SDS courses, whose timetable avoids overlaps. The courses in the second subrule are borrowed from other M.Sc.'s and may present schedule overlaps.

Course arxive by cohorts

Additional suggested courses

• Internship and Additional Training (3/6/9/12 credits)

These are flexible SDS activities that can be used for inserting in the study plan an Internship period (see page Internships for guidelines), or attendance of extra curricular courses, e.g., courses held by visiting professors outside other official courses. Combinations of the above are possible, subject to special approval by the the Executive Committee in accordance with the Internship Committee.

Further Information

Language

All courses listed above are taught in English, which is the official and working language of the M.Sc. See Admissions for the English proficiency required for applying.

Analysis

At the admission, based on the documentation provided by the applicant and on the interview, the Admission Committee assigns each student to either Analysis Course A or Analysis Course B. The Committee's decision aims at levelling the enrolled students' knowledge on the topic by the end of the first semester, allowing students without a strong background in Mathematics to enter smoothly the Program and develop the necessary intruments to complete it successfully. To this end, student assigned to Course B will also have to attend Tutorial Courses before the beginning of regular courses (see dates here). Exceptions on these decisions can be discussed with the Program Coordinators on a case-by-case basis upon request by the student.

Credits/hours conversion

The above indicated credits correspond to Italian CFU and to European ECTS. The typical courses lengths for this study plan based on the credits conversion into classes hours are as follows:

• 3 credits = 24 hours
• 6 credits = 48 hours
• 9 credits = 72 hours
• 12 credits = 96 hours

Classes are organised in two 12-week semesters, so a 6-credit course typically corresponds to 2 classes of 2 hours each per week, and a 9-credit course to 3 classes of 2 hours each per week.

Free credits

Freely credits can be used by the student to personalise the study plan according to personal interests. All courses available in that academic year at the University of Torino can be chosen, excluding courses whose content is already covered or contained in other courses of the present degree. This will be verified when the student's study plan is formally validated before the final defense. The students are encouraged to select as free credits the optional courses of this degree not included as first choice in the study plan. 

A list of the courses currently offered in English at the University of Torino is available here.

Thesis

The final examination consists in the discussion in front of an ad hoc Faculty Committee of a written dissertation elaborated by the student under the supervision and on a topic agreed with a Faculty member. The thesis can be written in connection with an internship in a public or private institution. See the page Thesis for more details.

Study plan for the cohort starting in a.y. 2023/24

Study plan for cohorts started on 2021/22 and 2022/23

Course arxive by cohorts

Study plan for cohorts started on aa.yy. 2016/17 to 2020/21

1^st Semester 

• Analysis A or B (9 credits)
• Probability theory (9 credits)
• Statistical Inference (9 credits)
• Programming for Data Science (3 credits)

• Stochastic Processes (6 credits)
• One course chosen between:
• Statistics for Stochastic Processes (6 credits)
• Stochastic Modelling for Statistical Applications (6 credits)
• Multivariate Statistical Analysis (6 credits)
• Databases and Algorithms (12 credits)
• One course freely chosen (6 credits)

• Stochastic Differential Equations (6 credits)
• One course chosen between:
• Bayesian Statistics (6 credits)
• Statistical Machine Learning (6 credits)
• Two courses chosen among (*):
• Complex Networks (6 credits)
• Computational Methods for Statistics (6 credits)
• Decisions and Uncertainty (6 credits)
• Econometrics (6 credits)
• Game Theory (6 credits)
  
• Information Theory (6 credits)
• Introduction to Data Mining (6 credits)
• Simulation (6 credits)
  
• Simulation Models for Economics (6 credits)
• One course freely chosen (6 credits)
  
• Thesis (24 credits)

Course arxive by cohorts

Study plan for the 2015/16 cohort

1^st Semester