Teaching
Teaching
Applied mathematics and their uses in science and engineering figure prominently in the ENSTA curriculum. The Applied Mathematics Department (UMA) is in charge of this curriculum. In concertation with the ENSTA management, we define the curriculum contents, create and provide part of the courses, and call upon outside contributors for the remaining ones. We propose basic courses in Senior year Bachelor, more-specialized (mandatory or optional) courses in second year (MSc year 1) as well as very specialized courses in the third and last year (MSc year 2).
See also:
- the HAL portal gathering lecture notes from UMA (under construction),
- a document about teaching applied mathematics at ENSTA Paris.
Senior year Bachelor (MSc year 1)
- AO101 Quadratic Optimization
- AO102 Dynamical Systems
- AOT11 Measure Theory and Integration in the Lebesgue sense -- Geometric and Functional Approaches
- AOT13 Differential geometry and geometric control
- MA102 Elementary tools of analysis for partial differential equations
- MA103 Introduction to partial differential equations discretization
- MA104 Functions of one complex variable
- PA102 Statistical physics
- PRB101 Probability: an introductory course
Mathematical Modelling of Engineering Systems (MSc year 1
- ANA201 Functional analysis
- ANA202 Spectral theory of the autoassistant operators
- ANN201 The finite element method
- ANN202 Analysis and finite element approximation of PDEs
- ANN203 Advanced numerical linear algebra: analysis and practice
- AUT201 Systems control
- IN207 Introduction to databases
- OPT201 Differentiable Optimisation
- OPT202 Advanced differentiable optimization
- PA201 Advanced Statistical Physics
- PA202 Plasmas physics
- PRB201 Markov chains
- PRB202 Martingales à temps discret
- PRB203 Introduction to Stochastic Calculus
- PRB210 Mathematics Models for Finance
- PRB211 Stochastic Models for Finance: the discrete time case
- PRB212 Stochastic Models for Finance: the continuous time case
- PRB220 Stochastic numerical methods
- PRB221 Monte-Carlo Methods
- PRB222 Projects of Computational Finance
- PRF-MA261 Preformation - Introduction to scientific computing
- RO201 Introduction to operations research
- RO202 Applied Operational Research
- RO203 Graphs, games and operational research
- SIM201 Scientific programming with C++
- SIM202 Numerical simulation
- SIM203 Introduction to high performance computing
- STA201 Statistical modelling
- STA202 Chronological series
- STA203 Statistical learning
- STA210 Statistical numerical methods
- STA211 Monte-Carlo Methods
- STA212 Statistical simulation methods
Mathematical Modelling of Engineering Systems (MSc year 2)
- AMS301 Parallel Scientific Computing
- AMS303 Méthodes variationnelles pour l'analyse de problèmes non coercifs
- AMS305 Inverse problems
- AMS306 Techniques de discrétisation avancées pour les problèmes d'évolution
- AMS307 Problèmes de diffractions en domaine non borné
- AMS308 Modèles mathématiques et leur discrétisation en électromagnétisme
- AMS309 Modeling of Plasmas and astrophysical Systems
- AMS310 Équations intégrales de frontière
- AMS311 Homogénéisation stochastique
- AMS312 Méthodes hybrides pour la diffraction à hautes fréquences
- AMS313 Sonia Fliss
- AMS314 Génération et adaptation de maillage pour le calcul scientifique
- ENT305-A Continuous optimization
- ENT306 Energy optimization project
- FQ301 Numerical Methods for PDEs in Finance
- FQ302 Lévy Processes and Applications in Finance
- FQ303 Calibration of the Local and Stochastic Volatility Models
- FQ304 Funding Value and Credit Valuation Adjustment
- FQ305 Risque de crédit
- FQ307 Elements of Stochastic Calculus
- FQ308 Avanced stochastic calculus
- MSE302 Introduction à l’imagerie médicale
- MSE303 Modélisation mathématique et estimation en biomécanique cardiaque – De la théorie aux applications médicales
- SOD311 Optimal control of ordinary differential equations ODEs
- SOD312 Markov decision processes: dynamic programming and applications
- SOD313 Optimization and approximation problems
- SOD314 Optimisation coopérative pour les sciences des données
- SOD321 Optimisation discrète
- SOD322 Recherche opérationnelle et données massives - part 1
- SOD323 Theory of complexity
- SOD324 Approximated methods
- SOD331 System identification for automatic
- SOD332 Geometric control
- SOD333 Optimal Bayesian filtering and particle approximation
- SOD334 Non linear time series