Big Data & Data Science training

Duration 3 days Get a quote

The Big Data revolution has generated a dramatic increase in data volumes, storage space and computing power to process them. Taking full advantage of this favorable environment, Machine Learning has significantly increased the efficiency of tools we use every day, such as search engines and referral systems. These fields of application, which are constantly expanding, today range from medicine to industry and the financial sector.

This training offers an extended presentation of Machine Learning, as it is used today in the professional world. It was designed to be accessible to an audience from a variety of backgrounds, the prerequisites being few.

The Machine Learning methodologies and its main algorithms will be presented, in their concepts as in their typical cases of use. Each time, implementations based on diversified domains will be proposed. They will take the form of labs implemented in Python language and using the most common libraries. Constructed in a didactic way, these labs will allow a tangible approach of the reality of Machine Learning: the predictive power of the models, like their limitations, will be studied notably through the quantitative analysis of the obtained results. The modern and very attractive subject of Deep Learning, based on neural networks, will be the subject of a first introduction.


  • Understanding Data Science
  • Understanding Machine Learning
  • To know how to model a Machine Learning problem
  • Types of Machine Learning
  • Problems of Machine Learning
  • Most used algorithms through application examples
  • Introduction to Deep Learning and Neural Networks


50% theory, 50% practise


  • Basic knowledge in algebra (matrices) and statistics
  • Knowledge in programming, ideally in Python

Target audience

Developers, future Data Scientists, Architects, Functionals, Project Managers

Financing in France

  • May be financed through OPCA (if financing covers all of the cost of the training)
  • Cannot be financed through the CPF


50% theory, 50% practise