Postgraduate course (M2), Université Paris Dauphine-PSL, MIDO, 2023
Some basic and classical machine learning and deep learning algorithms: Decision Trees, Random Forests, SVM, SVD, NNs, CNN, Auto Encoders, etc. There will be a final project: constructing a recommender system using SVD.
Undergraduate course (L1), Université Paris Dauphine-PSL, LSO, 2021
Undergraduate course (L2), Université Paris Dauphine-PSL, LSO, 2021
Graduate Level (M2), Université Paris Dauphine-PS, MIDO, 2020
This course aims to enable students to understand the organization of data within a relational database and to know how to manipulate and manage this data. The course will also introduce the topic of Big Data, highlighting the challenges it poses, as well as the solutions and technologies available for managing large volumes of data.
Undergraduate course (L2), Université Paris Dauphine-PSL, MIDO, 2020
Asymptotic comparison of algorithms: main complexity classes. Use of tree structures for search and sorting: binary trees and BSTs, balanced trees, heaps. Examples of advanced algorithms: integer and matrix multiplication, and exponentiation. Complexity theorem of recursive divide-and-conquer algorithms.