Introduction to data-science and machine learning with python


This learning track provides a first dive in the machine learning world with python. It starts with the basics of data-science (data-analysis, data-wrangling and data-visualization). Then we move to the basics of machine learning to finish with an introduction to deep learning.

Introduction to data-science with python

Data science is a rapidly evolving field at the intersection of statistics, computer science, and business acumen. Understanding data and its hidden patterns play a crucial role in decision-making and strategic planning in today's data-driven world. Python, due to its readability and a wide array of scientific libraries, is a widely used programming language in data science. This module aims to equip learners with fundamental concepts and practical skills of data science using Python.

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Introduction to machine learning with python

This course aims to introduce the principles and methods of machine learning (mainly supervised machine learning on tabular data) with Python. The first steps will be to use and assess trained models. Then the course will focus on the methods to train a model. Data loading and pre-processing, including feature engineering will also be covered as they are critical stages for successful model training. Basics of non-supervised learning will also be covered as a bonus.

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Introduction to deep learning

Deep learning methods have revolutionized the machine learning field. They have encountered tremendous success in computer vision, audio application or natural language processing. They draw their success, among other things, because they are able to provide automatic feature engineering thanks to their hidden layers. The goal of this course is to gain a first understanding of such models and learn how to train and use them. Transfer learning a standard technique to train models more efficiently will be covered.

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SKU: 10218 Categories: ,

Start date

October 19, 2023

End date

November 3, 2023

Language(s) of the training


Languages spoken by the coach(es)

English, French


Cetinsoy Laurent, Noura Benhajji



Learning Outcomes

  • Utilize Python libraries such as NumPy, pandas, and matplotlib for data manipulation, computations, and visualization.
  • Preprocess and manipulate datasets effectively for data analysis.
  • Interpret and represent complex data using Python’s data visualization techniques.
  • Solve practical, data-driven problems using Python.
  • Prepare tabular datasets for model training
  • Train standard supervised model for regression and classification
  • Use trained models in a simple dashboard application
  • Train deep learning model in simple setting
  • Do image classification with deep learning
  • Understand the basic theory of deep neural networks
  • Grasp the various subfields of deep learning


Introduction to data-science with python has a total duration of 14 hours and takes place over 2 days

  • 19-10-2023: 09:00 – 17:00
  • 20-10-2023: 09:00 – 17:00

Introduction to machine learning with python has a total duration of 21 hours and takes place over 3 days

  • 25-10-2023: 09:00 – 17:00
  • 26-10-2023: 09:00 – 17:00
  • 27-10-2023: 09:00 – 17:00

Introduction to deep learning has a total duration of 21 hours and takes place over 3 days

  • 31-10-2023: 09:00 – 17:00
  • 02-11-2023: 09:00 – 17:00
  • 03-11-2023: 09:00 – 17:00

Format and Location

This course takes place ON-SITE

Terres Rouges building
14, porte de France
L-4360 Esch/Alzette




  • Python for data-science
  • Basics of machine learning

Additional Info


This training does not have any assessment or exams; a certificate of participation will be issued to participants.

Esco Skills

inspect data analyse big data prepare visual data utilise machine learning data mining

Esco Occupations

data analyst data scientist data scientist