Artificial Intelligence and Big Data


IT systems of today record every new piece of data that comes their way. This results in a massive increase in the quantity of data available in digital form.

The big data thus collected forms large samples used to conduct statistical analyses or develop predictive models that would never have seen the light of day on small or medium-sized samples. These analyses use this data to highlight new associations, trends or predictions that constitute real added value for businesses or society.

Processing the hidden content in big data as comprehensively as possible is a real challenge for a computer engineer. Indeed, handling large volumes of data requires the use of specific tools and techniques designed to be operated on such a scale, for example parallelisation, optimisation and virtualisation. Furthermore, the complexity inherent to data means that the latter must be processed using specific algorithms which, for example, take into account a high number of interdependent variables and highlight the most relevant with regard to a given problem.

The IAMD Major aims at teaching computer engineers to understand the problems specific to a given profession to guide the development and implementation of an analysis process using complex and potentially voluminous data.

These skills typically correspond to those of a Data Scientist. In French, this is sometimes referred to as a data expert or specialist [expert / spécialiste des données]. IAMD therefore prepares students for the Data Scientist profession, as well as many other professions such as a Data Miner or Data Manager.
From a teaching perspective, this specialisation offers modules on artificial intelligence, data mining, text mining, statistics, data visualisation, and tangible projects with real data.

Various opportunities stem from the IAMD Major and these are on the rise as IAMD directly concerns activities associated with the notion of Big Data. Big Data is regarded highly by many businesses and in particular by IT companies (such as SAS, Oracle and Amazon). In addition to the latter, bodies owning or having access to data are also looking to transform this data using this type of approach (for example SFR, local authorities and the French national library).