The objec­tive of the IAD pro­gramme is to train engi­nee­ring stu­dents in the tech­niques and methods under­pin­ning Arti­fi­cial Intel­li­gence and Data Sciences in a broad conno­ta­tion. The fields cove­red are know­ledge engi­nee­ring, lear­ning pro­cesses, data engi­nee­ring and deci­sion sup­port methods.

Course contents

IAD trai­ning focusses spe­ci­fi­cal­ly on three areas: the consti­tu­tion and struc­tu­ring of data­bases or data ware­houses, with data inco­ming from some­times hete­ro­ge­neous sources or sys­tems; the exploi­ta­tion of data using data ana­ly­sis tools (data mining) and machine lear­ning; and know­ledge management.

Engi­neers taking the IAD pro­gramme the­re­fore acquire new skills in:

• in data­bases, data ware­houses, data dis­tri­bu­tion and cal­cu­la­tions (CC NF26),
• data ana­ly­sis and machine lear­ning: fac­to­rial ana­ly­sis, auto­ma­tic clas­si­fi­ca­tion, seg­men­ta­tion, dis­cri­mi­nant ana­ly­sis, deci­sion trees, arti­fi­cial neu­ral net­works, etc. (CCs SY09 and SY19),

• Know­ledge mana­ge­ment: know­ledge extrac­tion and mana­ge­ment, know­ledge capi­ta­li­sa­tion, indexing and infor­ma­tion retrie­val, rule-based and model-based rea­so­ning, reac­tive and cog­ni­tive agents, etc. (CCs IA03, IA04 and LO17).

The academic teaching team

The aca­de­mic tea­ching team com­prises lec­tu­rers from the CID team of the CNRS UTC Heu­dia­syc UMR7253 research labo­ra­to­ry. The research acti­vi­ties of the team are rela­ted to AI (arti­fi­cial intel­li­gence). The research car­ried out in CID concerns sta­tis­ti­cal lear­ning, uncer­tain­ty mana­ge­ment and know­ledge engi­nee­ring with appli­ca­tions to know­ledge capi­ta­li­sa­tion, path recom­men­da­tion and the scrip­ting of vir­tual environments.

Equipment

The courses are imple­men­ted via super­vi­sed ses­sions and pro­ject work, on UTC based machines or on dedi­ca­ted ser­vers for cer­tain courses.

Placements/internships and industrial relations

In addi­tion, confe­rences are orga­ni­zed each year to com­ple­ment the class­room courses and pro­vide a dif­ferent pers­pec­tive on cur­rent issues. Final­ly, a Peda­go­gi­cal Advi­so­ry Com­mit­tee brings toge­ther UTC tea­ching staff and exter­nal experts from indus­try and other edu­ca­tio­nal esta­blish­ments in order to adapt the content to deve­lop­ments ongoing in the field. The range of inter­n­ships offe­red is rich and varied.

International

Stu­dents who take the IAD pro­gramme are able to spend nume­rous semes­ters abroad (Cana­da, Swe­den, Spain, USA, Japan, etc.). They can also conti­nue their trai­ning during their stays abroad, as the part­ner ins­ti­tu­tions gene­ral­ly offer simi­lar or even com­ple­men­ta­ry courses to those of the UTC pro­gramme. A cer­tain num­ber of end-of-stu­dy pro­jects concern inter­na­tio­nal work.

Professional openings

The main job oppor­tu­ni­ties, among others, are:

• Data scien­tist. Desi­gn of lear­ning and ana­ly­ti­cal methods, eva­lua­tion of methods, aca­de­mic or indus­trial research, etc.;
• Data engi­neer. Imple­men­ta­tion of lear­ning methods, data pipe­line desi­gn, data ana­ly­sis, busi­ness intel­li­gence, etc.
• Know­ledge engi­neer. Know­ledge extrac­tion and mana­ge­ment, busi­ness pro­cess model­ling, know­ledge capi­ta­li­za­tion, web pro­gram­ming, etc.

The triple skills acqui­red in data science, data ware­house mana­ge­ment and know­ledge engi­nee­ring, all of which are high­ly valued by busi­ness sec­tor com­pa­nies, enable the gra­duate to hold a pro­fes­sion in a wide varie­ty of sec­tors of activity:

• for com­pa­nies spe­cia­li­zing in infor­ma­tion hand­ling tech­no­lo­gies, in par­ti­cu­lar soft­ware publi­shers (Das­sault, SAP, etc.);
• for com­pa­nies or admi­nis­tra­tions (banks, insu­rance com­pa­nies, indus­trial pro­duc­tion, dis­tri­bu­tion, tele­com­mu­ni­ca­tions, etc.);
• with IT ser­vices and engi­nee­ring com­pa­nies (SSIIs).

Contact and documentation

Res­pon­sable de la filière

Domi­tile Lourdeaux

 +33 (0)3 44 23 79 84

domitile.lourdeaux@hds.utc.fr

Res­pon­sable pédagogique

Meh­di Serairi

 +33 (0)3 44 23 44 75

mehdi.serairi@utc.fr

Coor­di­na­trice des stages

Maryam Ly

 +33 (0)3 44 23 52 37

maryam.ly@utc.fr

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