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

Master — Applied statistics

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

Sustainable Development Goals : 3Good health and well-being

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 400h30 hours per semester Lecture 10h30 Tutorial 10h30 Lab 6h00

Fundamental UEF 1 18 credits · Coefficient 9
  • Data Analysis (1) Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
  • Processes and Their Statistics Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
  • Descriptive Data Mining Techniques and Methods (1) Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
Methodological UEM 1 9 credits · Coefficient 5
  • Mathematical Statistics Lecture 1h30Tutorial 3h00 63h00 5 credits × 3
  • Applied Statistics in Healthcare Lecture 1h30Lab 1h30 45h00 4 credits × 2
Discovery UED 1 2 credits · Coefficient 2
  • Entrepreneurship Lecture 1h30Tutorial 1h30 45h00 2 credits × 2
Transversal UET 1 1 credit · Coefficient 1
  • English Lecture 1h30Tutorial 1h30 45h00 1 credit × 1

Semester total : 30 credits · 400h30 · Coefficient 17

Semester 2 M1

30 credits 393h30 hours per semester Lecture 10h00 Tutorial 6h00 Lab 11h00

Fundamental UEF 2 18 credits · Coefficient 9
  • Time Series Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
  • Exploratory Data Analysis Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
  • Linear Model Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
Methodological UEM 2 9 credits · Coefficient 5
  • Operations Research Lecture 1h30Tutorial 1h30Lab 1h00 56h00 5 credits × 3
  • Neural Networks 1 Lecture 1h30Lab 1h30 45h00 4 credits × 2
Discovery UED 2 2 credits · Coefficient 2
  • R Software Lecture 1h00Lab 2h00 45h00 2 credits × 2
Transversal UET 2 1 credit · Coefficient 1
  • Artificial Intelligence Applied to Statistics Lecture 1h30Lab 2h00 45h00 1 credit × 1

Semester total : 30 credits · 393h30 · Coefficient 17

Semester 3 M2

30 credits 371h00 hours per semester Lecture 11h30 Tutorial 5h30 Lab 8h00

Fundamental UEF 3 18 credits · Coefficient 9
  • Design of Experiments Lecture 1h30Tutorial 3h00 67h30 6 credits × 3
  • Predictive Data Mining Techniques and Methods (2) Lecture 1h30Tutorial 1h30Lab 1h30 67h30 6 credits × 3
  • Neural Networks (2) Lecture 3h00Lab 1h30 67h30 6 credits × 3
Methodological UEM 3 9 credits · Coefficient 5
  • Data Analysis (2) Lecture 1h30Tutorial 1h00Lab 1h30 56h00 5 credits × 3
  • Learning Theory Lecture 1h30Lab 1h30 45h00 4 credits × 2
Discovery UED 3 2 credits · Coefficient 2
  • Python Lecture 1h00Lab 2h00 45h00 2 credits × 2
Transversal UET 3 1 credit · Coefficient 1
  • LaTeX Lecture 1h30 22h30 1 credit × 1

Semester total : 30 credits · 371h00 · Coefficient 17

Semester 4 M2

30 credits 520h00 hours per semester Lecture 0h Tutorial 0h Lab 0h

End-of-studies project PFE 4 30 credits · Coefficient 30
  • Personal work 210h00 12 credits × 12
  • Internship in a Company 210h00 12 credits × 12
  • Dissertation 100h00 6 credits × 6

Semester total : 30 credits · 520h00 · Coefficient 30

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