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Vue d'ensemble
Sciences de la gestion : This course consists of two parts: (i) The first half of the course focuses on probabilistic and statistical foundations of data analytics. At the end of this part, students will have the mathematical knowledge in following topics: probabilities, random variables, the Central Limit Theorem; prior and posterior distributions, and Bayes鈥� rule; correlation, and Sampling. (ii) The second half of the course focuses on mathematical foundations of decision analytics. At the end of this part, students will have the mathematical knowledge in following topics: linear algebra; calculus of several variables; convexity; separating hyperplanes; unconstrained and constrained optimization; lagrange multipliers.
Terms: Hiver 2024, 脡t茅 2024
Instructors: Gumus, Mehmet (Winter) Gumus, Mehmet (Summer)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the fourth lecture day.
**No web drop allowed.
**Web withdrawal not applicable.
**Web ADD only
