Applied Data Analytics

Résumé de la formation

This course provides essential techniques, methodologies, and practical skills needed to extract meaningful insights from data. It is designed to be beneficial for a diverse range of doctoral students from various faculties at the UPCité. Key topics covered in the course include data science, data analytics, machine learning, deep learning, and data mining.

Format of lectures

The course will take place over a dedicated week in the fall, running from Monday to Friday in the mornings, from 10:00 AM to 13:00 PM, totalling approximately 15 hours. Instruction will be delivered through a combination of slides, Google Colab exercises, and questionnaires. On the final day, students will have the opportunity to present the analysis challenges related to their theses. The course will be conducted via Zoom.

S'inscrire

Programme

Monday

17/11/25

Tuesday

18/11/25

Wednesday

19/11/25

Thursday

20/11/25

Friday

21/11/25

10h00-11h20

Introduction
Objective of the course

10h00-11h20

Classic supervised Learning

10h00-11h20

Classic Supervised Learning

Regression

10h00-11h20

Neural Networks

10h00-11h20

Unsupervised Learning & Generative Models

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

Data preparation

 

11h30-13h00

Classic supervised Classification

11h30-13h00

Notebooks

 

11h30-13h00

Deep Learning

 

 

11h30-13h00

Students present their data analysis challenges
         
         
         
         

 

Formateurs et formatrices

Yvonne BECHERINI

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

Informations pratiques

La formation se tiendra du 17 novembre 2025 au 21 novembre 2025 en distanciel

Doctorat, Outils numériques

Public

Doctorants

Durée

5 jours

Langue

Anglais

Format

Distanciel

Code

DF25ADA

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