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Bachelor's degree in Mathematics Applied to Data Analysis and Decision - LMAD

Home › Programs › Bachelor’s Degree › Bachelor’s degree in Applied Mathematics
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Level

Bachelor's degree

Prerequisite

Baccalaureate

Credits

180 ECTS

Duration

6 semesters and Internship

Study mode

Initial training / Full time

Semestre 1
  • Algèbre 1
  • Analyse 1 
  • Base de données 
  • Programmation C 
  • Anglais 1
  • Atelier Programmation R
  • Séminaire 1
Semestre 2
  • Algèbre 2
  • Analyse 2
  • SGBD
  • Système d’information d’aide à la décision
  • Anglais 2
  • Atelier de programmation Python 1
  • Séminaire 2
Semestre 3
  • Algèbre 3
  • Analyse 3 
  • Intelligence artificielle 
  • Programmation C Avancé 
  • Atelier Python 2 
  • Anglais 3 
  • Séminaire 3
Semestre 4
  • Recherche Opérationnelle
  • Analyse 4
  • Introduction Big DATA
  • Programmation OO
  • Projet professionnel personnel
  • Atelier de programmation Python 3
  • Séminaire 4
Semestre 5
  • Probabilités
  • Calcul différentiel
  • Mathématiques discrètes
  • Analyse des données
  • Gestion de carrière
  • Atelier Data Science
  • Séminaire 5
Semestre 6
  • Analyse numérique
  • Statistiques
  • Equations différentielles
  • Projet fin d’études
Presentation
Admission
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Presentation

Objective

The world has become mathematical. Decision-making is based on the analysis of increasingly massive data – Big Data. The Bachelor’s degree in Mathematics Applied to Data Analysis and Decision Support calls on artificial intelligence and machine learning tools, as well as mathematical and statistical skills and know-how. This degree is aimed at graduates with a bachelor’s degree in mathematics, computer science, experimental sciences, technical sciences or equivalent.

Content

  • MATHEMATICS & STATISTICS : Data analysis, Discrete& convex optimization, statistical analysis, regression & predictive models models, Stochastic processes
  • BUSINESS INTELLIGENCE : Programming (Python), Databases, Data Warehouse, Data Mining, Big Data, Artificial Intelligence, Machine Learning
  • SOFT SKILLS : Seminars, Personal Development, Business Games, Languages, etc.
  • PROFESSIONAL PROJECT : Internships, PFE, Integrated projects, Company visits, Workshops, Case studies, etc.

Skills

  • Help organizations create value or innovate in respective sectors through their decisions based on mathematical rigor & inferred statistical techniques.
  • Master the analysis and processing of massive data (Big Data).
  • Master data science programming languages.
  • Assess profitability and manage risk for financial products.
  • Implement data mining and exploitation methods.
  • Organize and supervise surveys and polls.
  • Assist in the digital transformation of companies.
  • Ensure product quality

Jobs / Careers

  • Data Analyst
  • Insurance Actuarial Analyst
  • Front Office Financial Market
  • Credit & Bank Risk Analyst
  • Data Miner / Data Scientist
  • BI Expert
  • Business Analyst
  • Statistician

Activity area

  • IT service companies
  • Software publishers
  • Banks & Insurance
  • Commercial & industrial companies

Professional partnerships

> Digital service companies > Banks & Insurance > Consulting firms

Subject per semester

Semester 1
  • Algebra I
  • Analysis I
  • Databases
  • C programming
  • English 1
  • R programming
  • Seminar 1
Semester 2
  • Algebra II
  • Analysis II
  • Database management systems
  • Business intelligence
  • English II
  • Python programming I
  • Seminar 2
Semester 3
  • Algebra III
  • Analysis III
  • Artificial intelligence
  • C programming advanced
  • Python programming II
  • English III
  • Seminar III
Semester 4
  • Operational research
  • Analysis IV
  • Big data analytics
  • Object oriented programming
  • Personal professional project
  • Python programming III
  • Seminar IV
Semester 5
  • Probability
  • Differential calculus
  • Discrete mathematics
  • Data analysis
  • Career management
  • Data science capstone
  • Seminar V
Semester 6
  • Numeric analysis
  • Statistics
  • Differential equations
Admission

This bachelor is intended for bachelors, in Computer Science, Economics and Management, Mathematics, Experimental Sciences, Technology and any equivalent diploma. Access to the Bachelor in Applied Mathematics to Data Analysis and Decision Aid M (AD) ² will be possible for candidates from the above-mentioned training courses, after an entrance examination.

Terms of Access 

Access to L2 :

Any student who has validated his/her first year in a mathematics bachelor or his/her first scientific preparatory year, subject to validation of the file by the Director of Studies.

Access to L3 :

Any student who has passed the national entrance exam to engineering schools or who has validated his/her first two years in a mathematical license, subject to validation of the file by the Director of Studies.

 

7 383,177 DT HT + 7% de TVA = 7 900,000 DT TTC

The issuance of the diploma is also subject to obtaining the B2 level in French and English.

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