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Study plan for the cohort starting in a.y. 2021/22

(check also International Visiting Professors foreseen for the next a.y.)
 
1st Year
1st Semester 
2nd Semester 
2nd Year (each course page indicates the semester)

Additional courses

  • Internship and Additional Training (3 credits)
  • Internship and Additional Training (6 credits)

These courses can be used as free credits (in place of the above courses freely chosen) for inserting in the study plan an Internship period, or attendance to extra curricular courses, like courses held by visiting professors outside other official courses, or additional IT training, or combinations thereof. These are subject to special approval by the Internship Committee.

 

Examples of personalised study plans

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

The two courses freely chosen correspond to 6+6 free credits that can be used by the student to personalise her/his study plan according to personal interests. The free credits can be used for choosing any course among all those available in that academic year at the University of Torino, excluding those 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.

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

The students are encouraged to select as free credits the optional courses of this degree not included as first choice in the study plan. For example, if course A is chosen from the two-items list (A,B), then course B can also be included in the study plan by using the free credits.

(*) The second year courses of the long item list can be anticipated to the first year of studies only as free credits.

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 2020/2021 cohort

 
1st Year
1st Semester 
2nd Semester 
2nd Year (each course page indicates the semester)

Course arxive by cohorts

 

Study plan for the 2019/2020 cohort

 
1st Year
1st Semester 
  • Analysis A or B (9 credits)
  • Probability Theory (9 credits)
  • Statistical Inference (9 credits)
  • Programming for Data Science (3 credits)
2nd Semester 
  • 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)
2nd Year (each course page indicates the semester)
  • 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 2018/2019 cohort

1st Year
1st Semester 
  • Analysis (9 credits)
  • Probability Theory (9 credits)
  • Statistical Inference (9 credits)
  • Programming for Data Science (3 credits)
2nd Semester 
  • 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)
2nd Year (each course page indicates the semester)
  • 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 2017/2018 cohort

1st Year

1st Semester 

  • Analysis (9 credits)
  • Probability Theory (9 credits)
  • Statistical Inference (9 credits)
  • Programming for Data Science (3 credits)

2nd Semester 

  • 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)

 

2nd Year (each course page indicates the semester)

 

  • 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 2016/2017 cohort

1st Year

1st Semester 

  • Analysis* (9 credits)
  • Probability Theory (9 credits)
  • Statistical Inference (9 credits)
  • Programming for Data Science (3 credits)
2nd Semester 
  • 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)
2nd Year
  • 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 2015/2016 cohort

1st Year

1st Semester 

  • Analysis* (9 credits)
  • Probability Theory (9 credits)
  • Statistical Inference (9 credits)
  • Programming for Data Science (3 credits)

2nd Semester 

  • 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)
2nd Year
  • Stochastic Differential Equations (6 credits)
  • One course chosen between:
    • Bayesian Nonparametric Statistics (6 credits)
    • Statistical Machine Learning (6 credits)
  • Two courses chosen among:
    • Complex Networks (6 credits)
    • Decision Theory (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

Last update: 30/06/2021 17:58
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