Data Science - Foundations & Machine Learning

Formation inter-entreprise

À qui s'adresse la formation?

Employees, adults in career transition, or professionals aiming to move into roles such as Data Scientist, Advanced Data Analyst, or Machine Learning Engineer; profiles from IT, science, mathematics, engineering, or business analytics backgrounds.

Niveau atteint

Intermédiaire

Durée

96,00 heure(s)

Langues(s) de prestation

EN

Prochaine session

03.02.2026
Lieu
Esch-sur-Alzette

Prérequis

Basic computer skills, knowledge of logic, mathematics, and statistics. Ideally, participants should have completed a data analyst module or equivalent

Objectifs

At the end of the training, participants will be able to:

  • Install and use a Python environment for data science
  • Manipulate data with fundamental tools (Anaconda, Jupyter, Pandas)
  • Master the mathematical foundations necessary for machine learning
  • Implement and evaluate different supervised learning models
  • Work on artificial neural networks
  • Apply unsupervised learning
  • Visualise multidimensional data
  • Complete a comprehensive data science project and defend it

Contenu

Software basic programming / Mathematics / Machine Learning / Final Project

Points abordés

Module 1 | Software basic programming |16h

  • Anaconda
  • Jupyter
  • Python

Module 2 | Mathematics | 16h

Module 3 | Machine Learning | 48h

  • Introduction Basics concepts and notations
  • Basics models for supervised learning
  • Multilayer Artificial Neural Networks
  • Unsupervised Learning
  • Visualising High-dimensional Data

Module 4 | Final Project | 24 h

Méthodes pédagogiques

The approach combines theory, hands-on exercises, and an individual project, with interactive discussions to encourage practical application of the skills learned.

Certificat, diplôme

Training Certificate

Prochaine session

Date
Ville
Language & prix
03.02.2026

12.05.2026
Esch-sur-Alzette
EN

Mode d'organisation

Cancellation:
In case of cancellation or absence from the course, the registration fees are fully due if the cancellation is not made at least 72 hours before the start of the course. Absences properly justified with a medical certificate entitle the participant to a full refund of the registration fees.

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