Advanced Applied Data Analytics

Résumé de la formation

This course is the second part of the diiP course “Applied Data Analytics.” The first part covers basic techniques, methodologies, and practical skills for data analysis. The second part delves into more advanced topics in Machine Learning and Deep Learning (see schedule below).
Like the first part, this course is intended for a variety of doctoral students from several faculties at UPCité. Key topics include data science, data analysis, machine learning, deep learning, and data mining.

S'inscrire

Programme

Monday

12/01/26

Tuesday

13/01/26

Wednesday 14/01/26

Thursday 15/01/26

Friday

16/01/26

10h00-11h20

Introduction
Objective of the course (Review of some basic topics)

10h00-11h20

 

Transformers

10h00-11h20

Graph Neural Networks

10h00-11h20

Probabilistic Modelling

 

10h00-11h20

Probabilistic Modelling

 

11h20-11h30

Break and

Poll ☕

11h20-11h30

Break and

Poll ☕

11h20-11h30

Break and

Poll ☕

11h20-11h30

Break and

Poll ☕

11h20-11h30

Break and

Poll  ☕

11h30-13h00

Generative Adversarial Networks

11h30-13h00

Graph Neural Networks

 

11h30-13h00

Self-supervised Learning

11h30-13h00

Probabilistic Modelling

11h30-13h00

Probabilistic Modelling

 

 

Formateurs et formatrices

Formateur : Yvonne Becherini

Email (contact pédagogique): becherini@u-paris.fr

Informations pratiques

La formation se tiendra du 12 au 16 janvier 2026

Formation en distanciel

Outils numériques

Public

Doctorants ayant suivi Applied Data Analytics

Durée

15 heures

Langue

Anglais

Format

Distanciel

Code

DF25ONAA

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