Teaching

Courses taught at Sorbonne University (188.5h):

Python programming (LU1IN011, TD/TP, 56h)
• Students: L1
• Notions: Variables, expressions, functions, alternatives, loops, differents types of data (lists, tables, dictionnaries, ensembles, intervals, strings), recursion, procedures, complexity, introduction to object-oriented programming

C programming (LU1IN002, TP, 66.5h)
• Students: L1
• Notions: Physical interfaces, how computers work, pointers and memory management, differents types of data (structures, lists, linked lists, tables, hash tables, string), pointer and string arithmetic, recursion

Data science (LU1INMA1, TP, 36.75h)
• Students: L1
• Notions: Discrete and continuous (random) variables, correlation and regression (covariance, regression line), unsupervised classification (automatic definition of a typology, k-means algorithm), numerical methods (optimization, finding the root or minimum of a function), inference (parameter estimation, maximum likelihood method), parametric supervised classification (conditional distribution, Bayes formula), non-parametric supervised classification (optimality of Bayes classifier, k-nearest neighbor algorithm)

Relational databases (LU2IN009, TP, 19.25h)
• Students: L2
• Notions: Entity-association model, transformation rules to relational model, relational algebra, relational calculus, data queries with SQL, data definition and manipulation languages, integrity constraints, programming in PL/SQL, triggers

Innovation management (MU5MN027, TD, 10h)
• Students: M2 (EPI Sciences et Santé)
• Supervision of students in apprenticeships