Email : fac.sciencesexactes@umc.edu.dz Facebook Twitter
University Frères Mentouri Constantine 1
Faculty of Exact Sciences

Master — Probability, statistics and applications

Mathematics and Computer Science · Mathematics · Academic year 2026-2027

View the programme outline (PDF)

Master, year 1 Semester 1 Semester 2
Master, year 2 Semester 3 Semester 4
How to read this table
  • UE : teaching unit, a group of subjects (fundamental, methodological, discovery, transversal).
  • Lecture · Tutorial · Lab : weekly hours: lectures, tutorials, lab work.
  • Coefficient / Credits : weight of the subject in the average, and credits earned when it is passed (30 per semester).
  • Semester hours (15 weeks) : total supervised hours over the semester (15 weeks × weekly hours).
  • Personal work : "Other": additional personal work by the student, unsupervised.

Semester 1 M1

30 credits 357h00 hours per semester Lecture 15h00 Tutorial 7h30 Lab 3h00

Fundamental UEF 1 18 credits · Coefficient 10
  • Advanced Probability Lecture 3h00Tutorial 1h30 63h00 5 credits × 3 40% Continuous assessment · 60% Exam
  • Complements of Measure Theory Lecture 1h30Tutorial 1h30 42h00 4 credits × 2 40% Continuous assessment · 60% Exam
  • Inferential Statistics 1 Lecture 3h00Tutorial 1h30 63h00 5 credits × 3 40% Continuous assessment · 60% Exam
  • Data Analysis Lecture 1h30Tutorial 1h30 42h00 4 credits × 2 40% Continuous assessment · 60% Exam
Methodological UEM 1 9 credits · Coefficient 5
  • Programming with R / Python Lecture 1h30Lab 1h30 42h00 4 credits × 2 40% Continuous assessment · 60% Exam
  • Extreme Value Statistics Lecture 1h30Tutorial 1h30 42h00 5 credits × 3 40% Continuous assessment · 60% Exam
Discovery UED 1 2 credits · Coefficient 2
  • Mathematical Modelling Lecture 1h30Lab 1h30 42h00 2 credits × 2 40% Continuous assessment · 60% Exam
Transversal UET 1 1 credit · Coefficient 1
  • Choose 1 subject among 2
  • Entrepreneurship Lecture 1h30 21h00 1 credit × 1 100% Exam
    Un module à choisir parmi les deux proposés.
  • Ethics of Artificial Intelligence Lecture 1h30 21h00 1 credit × 1 100% Exam
    Un module à choisir parmi les deux proposés.

Semester total : 30 credits · 357h00 · Coefficient 18

Semester 2 M1

30 credits 357h00 hours per semester Lecture 15h00 Tutorial 9h00 Lab 1h30

Fundamental UEF 2 18 credits · Coefficient 9
  • Stochastic Processes Lecture 3h00Tutorial 1h30 63h00 6 credits × 3 40% Continuous assessment · 60% Exam
  • Inferential Statistics 2 Lecture 3h00Tutorial 1h30 63h00 6 credits × 3 40% Continuous assessment · 60% Exam
  • Martingale Theory Lecture 3h00Tutorial 1h30 63h00 6 credits × 3 40% Continuous assessment · 60% Exam
Methodological UEM 2 9 credits · Coefficient 6
  • Simulation and Monte Carlo Methods Lecture 1h30Tutorial 1h30Lab 1h30 63h00 5 credits × 3 40% Continuous assessment · 60% Exam
  • Linear Models Lecture 1h30Tutorial 1h30 42h00 4 credits × 3 40% Continuous assessment · 60% Exam
Discovery UED 2 1 credit · Coefficient 1
  • Choose 1 subject among 2
  • Scientific Computing Lecture 1h30 21h00 1 credit × 1 40% Continuous assessment · 60% Exam
    Un module au choix parmi les deux proposés.
  • Neural Networks Lecture 1h30 21h00 1 credit × 1 40% Continuous assessment · 60% Exam
    Un module au choix parmi les deux proposés.
Transversal UET 2 2 credits · Coefficient 2
  • Lean Startup Lecture 1h30Tutorial 1h30 42h00 2 credits × 2 80% Continuous assessment · 20% Exam

Semester total : 30 credits · 357h00 · Coefficient 18

Semester 3 M2

30 credits 357h00 hours per semester Lecture 16h30 Tutorial 7h30 Lab 1h30

Fundamental UEF 3 18 credits · Coefficient 9
  • Nonparametric Statistics Lecture 3h00Tutorial 1h30 63h00 6 credits × 3 40% Continuous assessment · 60% Exam
  • Time Series Lecture 3h00Tutorial 1h30 63h00 6 credits × 3 40% Continuous assessment · 60% Exam
  • Stochastic Calculus Lecture 3h00Tutorial 1h30 63h00 6 credits × 3 40% Continuous assessment · 60% Exam
Methodological UEM 3 9 credits · Coefficient 5
  • Systems Reliability Lecture 3h00Tutorial 1h30 63h00 5 credits × 3 40% Continuous assessment · 60% Exam
  • Survival Analysis Lecture 1h30Tutorial 1h30 42h00 4 credits × 2 40% Continuous assessment · 60% Exam
Discovery UED 3 2 credits · Coefficient 2
  • Choose 1 subject among 2
  • Machine Learning Lecture 1h30Lab 1h30 42h00 2 credits × 2 40% Continuous assessment · 60% Exam
    Un module à choisir parmi les deux proposés.
  • Deep Learning Lecture 1h30Lab 1h30 42h00 2 credits × 2 40% Continuous assessment · 60% Exam
    Un module à choisir parmi les deux proposés.
Transversal UET 3 1 credit · Coefficient 1
  • Research Methodology and Scientific Writing Lecture 1h30 21h00 1 credit × 1 100% Exam

Semester total : 30 credits · 357h00 · Coefficient 17

Semester 4 M2

30 credits 750h00 hours per semester Lecture 0h Tutorial 0h Lab 0h

Shared with : Mathematical analysis and applications · Partial differential equations and applications

End-of-studies project PFE 4 30 credits · Coefficient 17
  • Final Project with Dissertation 750h00 30 credits × 17
    Projet de fin d'études sanctionné par un mémoire.

Semester total : 30 credits · 750h00 · Coefficient 17

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