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Objectives : 3 years. The training includes 1800 hours of teaching and 600 hours of tutored projects, divided into 6 semesters, as well as 22 to 26 weeks of internship.
The objective of the training being to train students in the field of data science, the disciplines taught are, in order of importance, statistics, computer science, economics and management, communication and English.
Degree Level (EU) : 6 - (EQC level or equivalent)
Prerequisites : General baccalaureates: Mathematics, Digital and Computer Sciences, Engineering Sciences, Economic and Social Sciences, Life and Earth Sciences, Physics-Chemistry.
Technological baccalaureates: STI2D.
Acquired skills during the training : The skills common to the 2 courses are:
Process data for decision-making purposes, by intervening at all stages of the data life cycle (insertion, modification, extraction, deletion)
Analyze data statistically, highlighting major trends and key information, and implementing the techniques identified and adapted to the expectations of the client or the decision-making body
Enhance a production in a professional context, by interpreting and contextualizing the results (quotations, verification of sources, critical thinking) and using the appropriate form of restitution
The skill specific to course 1 "data science: exploration and statistical modelling" which broadens students' skills in modeling and statistical analysis:
Model the data in a statistical framework, by choosing the model adapted to the situation, by controlling the quality of the model and by adapting to the specificities (data, issues, methods) of a particular field of application (health, marketing, insurance, quality, socio-demography, etc.)
The skill specific to course 2 “data sciences: visualization, design of decision-making tools” which specializes the student in the development of decision-making solutions and visual restitutions (DataViz):
Develop a decision-making tool, by implementing a data structure adapted to their characteristics (type, volume, etc.), and by creating visualization solutions specific to business data.
Targeted careers : Statistical Researcher, Statistical Developer, Data-Analyst, Statistical Assistant, Data-scientist Assistant, Marketing Researcher Assistant, Analysis and Reporting Officer.
Data-analyst - Decision-making/BI developer, Analysis and reporting manager, Data-manager - Data manager, AMOA project manager.
These professions can be exercised in different sectors of activity where the analysis of data and the production of statistical models are required:
Health
Public (security, employment, transport, etc.)
Bank
Marketing
Aeronautics
Sale
Human ressources
Logistics
etc
Duration and terms : 3 years. The training includes 1800 hours of teaching and 600 hours of tutored projects, divided into 6 semesters, as well as 22 to 26 weeks of internship.
Dedicated web site : https://iut.univ-perp.fr/fr/formations/dut/statistique-et-informatique-decisionnelle-stid#presentation