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UE Learning, Probabilities and Causality

  • Level

    Baccalaureate +5

  • ECTS

    6 credits

  • Component

    UFR IM2AG (informatique, mathématiques et mathématiques appliquées)

  • Semester

    Automne

Description

Causality is at the core of our vision of the world and of the way we reason. It has long been recognized as an important concept and was already mentioned in the ancient Hindu scriptures: “Cause is the effect concealed, effect is the cause revealed”. Even Democritus famously proclaimed that he would rather discover a causal relation than be the king of presumably the wealthiest empire of his time. Nowadays, causality is seen as an ideal way to explain observed phenomena and to provide tools to reason on possible outcomes of interventions and what-if experiments, which are central to counterfactual reasoning, as ‘‘what if this patient had been given this particular treatment?’’

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Objectives

The main aim of this course is to provide the principles and tools to understand and master learning models based on probabilities and causality.

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Course parts

  • CMLectures (CM)36h
  • Practical workPractical work (TP)18h

Recommended prerequisites

Probability and statistics background.

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