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WIS, the [tech] school for digital expertise

Learning method

Mastering digital professions today means having a head start on all fronts: yours, those of constantly evolving technology, and those of the companies that await you tomorrow. And for that, there's no question of choice.

For us, teaching digital expertise means inevitably mastering the technique.

At WIS, dual expertise is our strength, and it will be yours tomorrow to be operational. Our digital school trains strategists who analyze, recommend, advise, and anticipate the challenges facing companies.

Choosing the WIS digital school also means choosing proximity by joining one of our 13 campuses spread across the country.

We accompany you to become experts in development, UX, data, IT... to tomorrow lead and carry out large-scale digital projects.

Recognized diplomas

  • Bachelor Chef de projet digital - full french
  • Parcours Expertise Digitale - full french

Innovation Lab

My DIL, a digital innovation laboratory

My DIL is an experimentation laboratory dedicated to learners on coding, digital and connected objects, data, and artificial intelligence.

It is both a training center, a place for exchange and meeting to develop, accelerate, co-construct, imagine uses, and foster the emergence of innovative projects through collaboration between learners, speakers, and professionals.


A laboratory of big data technologies and tools

MyDataLab is our technological laboratory of Data, this "black gold of the 21st-century digital world."

It is integrated within MyDIL, the digital experimentation laboratory.

WIS learners work on building a Data Lake that allows the aggregation of structured or unstructured data sets, continuously enriching them with new experiments and exploiting the results.

With the assistance of data experts, they exploit the various datasets necessary and grasp the evolution of Big Data or Artificial Intelligence throughout their journey.

They test Machine Learning algorithms and deploy Data Science or AI projects:

  • Collecting heterogeneous data (web, connected objects, data mining...)
  • Processing raw structured and unstructured data to transform them into actionable information
  • Analyzing, building, and sharing data mining reporting models.