DATA SEO LABS is a Datadock referenced training organization.


Upcoming training

Paris, FR

(in French)

1290€ HT

2 days to
experiment machine learning

This machine learning training has been designed to be accessible to all, without any technical knowledge and with NO pre-requisites. From the very first hour, you will be directly immersed in a real Machine Learning project, taken from the world of digital marketing. You will be guided step by step to make your project a success.

Data analysis and preparation, choice of algorithms, creation of a prediction model, you will learn all this during these 2 days in which each module is designed to allow you to develop new concrete skills. Ready to take a leap into the future?

8 places per session

2 trainers at your side

2 days in immersion

Access to notebooks

Machine learning
training program

Module 1

Your first prediction
Launch your 1st machine learning classification algorithm, and discover how to use Jupyter Notebooks.

Module 2

Intro to Machine Learning
Through concrete business examples, discover the world of machine learning, its challenges and its major concepts.

Module 3

Machine Learning workflow
From A to Z, go through the main stages of a Machine Learning project and develop the right reflexes.

Module 4

Data preparation and analysis
Discover data mining techniques, and learn how to prepare them for the creation of a predictive model.

Module 5

Regression, Decision tree, Random forest… Discover the main algoes of ML and how they work (case study).

Module 6

Model performance
After some revisions of the statistical databases, discover how to evaluate the effectiveness of your prediction

Module 7

Data Scientist’s tips
How to avoid the pitfalls of machine learning and boost the performance of your model? Learn to think in data scientist

DATA SEO LABS Certification
Test your new skills and obtain your Level 1 Machine Learning certification. Our prediction: your success!

150+ companies
trust us

oui sncf
leroy merlin
ovh cloud
fnac darty
search foresight
remi vincent

The trainers

Rémi Bacha
Passionate about R&D and on the lookout for innovations in data science, Rémi Bacha is co-founder of DATA SEO LABS. He worked for 7 years at OVH Cloud as SEO manager and then Data Scientist.
Vincent Terrasi
Pioneer of the Data SEO approach, Vincent Terrasi is co-founder of DATA SEO LABS and product manager for an SEO software publisher. A former entrepreneur, he was also Data Marketing Manager at M6 and OVH Cloud.
Who is
machine learning training for ?

The Machine Learning course is designed for digital marketing and e-commerce professionals who want to discover the opportunities offered by artificial intelligence and plunge into the incredible world of prediction.

  • SEO / SEA experts
  • Traffic manager
  • Digital marketer
  • Product Manager
  • Project Manager
  • Digital analyst
  • Data analyst
  • Web analyst
  • Head of e-commerce
  • CEO / Startup founder
  • Developer
  • Data scientist
  • Online acquisition manager
  • Consultant
  • Business developer
asked questions

No. Most of the TPs that require computing power take place in the cloud. So you can come with your usual laptop.

Yes, Machine Learning is ideal for giving your digital marketing teams new reflexes to exploit the full potential of the data at their disposal. At the end of this training they will be able to manage a complete machine learning project and to manage each step of it from an operational point of view. Thanks to the learning machine, IT systems today can learn to predict the future using data: a competitive advantage for all digital marketing specialists who will be able to use it.

By privatizing the training, you ensure your teams a rapid and homogeneous increase in skills. All the examples and TP are thus adapted to your own websites to encourage direct exploitation of the benefits of the training.
Would you like to organise a Machine Learning training course in your company? Contact us

Yes, the Machine Learning certification attests to your skills in the management of a machine learning project: choice of data, preparation of data, choice of algorithms, exploitation and evaluation of the results produced by the algorithms.