Machine Learning with Python (1-day online workshop)



  • basic knowledge of Python programming.
  • basic knowledge of university mathematics (Calculus, Probability, Statistics).


  • The Machine Learning workflow.
  • Exploratory data analysis.
  • Pipelines for classification and regression.
  • Decision trees and ensemble models.
  • Model explainability.
  • Unsupervised learning: clustering and dimensionality reduction.


In this course, we will go to the basics of Machine Learning. At the end of the course, you would be familiar with the scikit-learn machine learning library.

Note: All trainings are in English language.

Additional information


January 12th, 2024, 9:00-16:00 CET (online)

Author: Pablo Maldonado

I am a consultant, technical trainer and lecturer in automation, data science and AI. My students, either at universities or companies, appreciate my hands-on approach coming from my experience at several projects across industries like financial services, marketing, and HR. Since 2017, I have been leading workshops for 30+ clients in 10+ countries including major companies such as Shell, Renault, PwC, O’Reilly Media, O2, La Poste, as well as institutions like the European Investment Bank, the Czech National Bank, the Australian Government, and many others. I have written a couple books (on Shiny, and on Deep Learning). I hold a PhD in Applied Mathematics from the Sorbonne Université in Paris, with a specialization in Game Theory and Markov Decision Processes.

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