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Informatique et Mathématiques appliquées
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> Formation > Cursus ingénieur

Probability for computer science - 4MM1PPI

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  • Number of hours

    • Lectures : 9.0
    • Tutorials : 9.0
    ECTS : 2.0

Goals

This course is an introduction with examples to probability models and methods useful in computer science. It gives theoretical material in probability and statistics and presents applications in the modelling and assessment of computer systems.

Contact Jean-Baptiste DURAND

Content

1. Conditional probability. Random vectors.
2. Simulation algorithms.
3. Random processes. Poisson processes.
4. Markov chains and processes.



Prerequisites

Applied Probability 1 (1st year).
Statistical Principles and Methods (2nd year).

Tests

Give kind of exam for session 1 and session 2: written, allowed documents or not, oral, practical work, reports, plan, vivas



N1 = 0.5 * E1 + 0.4 * P1 + 0.1 * A1
N2 = O

Additional Information

Curriculum->Work Study Education->Alternance 2eme annee

Bibliography

S.M. ROSS : Probability Models for Computer Science, Academic Press, 2001.
K.S. TRIVEDI : Probability and Statistics with Reliability, Queuing and Computer Science Applications, Wiley, 2002.

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Date of update January 15, 2017

Grenoble INP Institut d'ingénierie Univ. Grenoble Alpes