Component
Faculty of Law, Economics & Management, Faculty of Science & Technology
Location(s)
Orleans
Presentation
The Artificial Intelligence: Data and Organizational Sciences double degree leads to the simultaneous award of two bachelor's degrees: one in computer science, the other in economics and management.
This demanding, selective program prepares students for further study in university Masters programs, engineering schools or business schools. Its aim is to train tomorrow's decision-makers to master the data processing techniques that are essential for decision-making in public and private organizations (governments, local authorities, non-governmental organizations, businesses).
This course is for anyone who enjoys taking on challenges, analyzing, modeling and solving complex problems. It requires a solid grounding in mathematics. A marked interest in programming, a keen curiosity for artificial intelligence, a taste for using digital tools and a desire to embark on a multi-disciplinary curriculum are all appreciated.
Useful contacts
UFR DEG International Relations Office :
https://www.univ-orleans.fr/fr/deg/international
international.deg@univ-orleans.fr
Tel: +33(0) 2 38 49 47 30
ORIENTATION AND
PROFESSIONAL INTEGRATION
DOIP
02 38 41 71 72
doip[at]univ-orleans.fr
Organization
Special features
The double license takes place in small groups.
A research project on cross-disciplinary themes is expected at the end of each academic year.
Program
The Artificial Intelligence: Data and Organizational Sciences double degree is built around core courses in mathematics, computer science and economics, and applied courses in artificial intelligence, data processing and analysis, as well as English. It is based on courses taught in the economics and management degree and the computer science degree, supplemented by specific courses in artificial intelligence, data science and organizational science.
With a limited capacity of 20 places, the program offers excellent study conditions. High selectivity guarantees a stimulating and enriching learning environment. The double bachelor's degree combines a traditional teaching approach for the fundamentals and a project-based approach for applied teaching.
Double degree Economics Computer science
|
Teaching unit |
Coefficient/Credits |
Hours Lecture courses |
Course TD or TP or CTD |
|---|---|---|---|
|
1st year |
|
|
|
|
Semester 1 |
|
|
|
|
Economics core curriculum |
|
|
|
|
Principles of economics |
4 |
30 |
- |
|
Organization management |
4 |
30 |
- |
|
Macroeconomics I |
4 |
30 |
15 TD |
|
English 1 |
2 |
- |
15 TD |
|
IT core curriculum |
|
|
|
|
Integration course: Introduction to Programming |
- |
- |
- |
|
Programming and Algorithms |
8 |
20 |
20 TD 16 TP |
|
Logic and demonstration |
6 |
12 |
12 TD 6 TP |
|
Dual degree courses |
|
|
|
|
Analysis I |
9 |
18 |
40 TD |
|
Algebra |
4 |
- |
36 CTD |
|
Introduction to AI |
3 |
15 |
15 TP |
|
Semester 2 |
|
|
|
|
Economics core curriculum |
|
|
|
|
Microeconomics I |
10 |
- |
40 CTD |
|
Statistics for economics and management |
10 |
- |
30 CTD |
|
Critical analysis of digitization and ethics |
4 |
12 |
- |
|
English 2 |
4 |
- |
20 TD |
|
IT core curriculum |
|
|
|
|
Mathematics for Computer Science |
8 |
20 |
40 TD |
|
Discrete mathematics |
6 |
12 |
18 TD |
|
Fundamentals of databases |
6 |
12 |
18 TD |
|
Algorithms and Programming |
8 |
20 |
30 TD 16 TP |
|
Dual degree courses |
|
|
|
|
Eco-Datalab data project |
2 |
- |
- |
|
Internship (optional) |
- |
- |
- |
|
Trade conferences |
- |
- |
- |
|
2nd year |
|
|
|
|
Semester 3 |
|
|
|
|
Economics core curriculum |
|
|
|
|
Macroeconomics II |
8 |
24 |
15 TD |
|
Microeconomics II |
8 |
30 |
15 TD |
|
Intermediaries and financial markets |
6 |
24 |
- |
|
English 3 |
6 |
- |
20 CTD |
|
IT core curriculum |
|
|
|
|
Databases |
9 |
15 |
20 TD 10 TP |
|
Object-oriented programming I |
10 |
20 |
20 TD 20 TP |
|
Automata, Languages and Logic |
9 |
20 |
20 TD 10 TP |
|
Dual degree courses |
|
|
|
|
Hackaton |
2 |
- |
- |
|
Semester 4 |
|
|
|
|
Economics core curriculum |
|
|
|
|
Probability and Random Variables |
6 |
- |
36 CTD |
|
Economic Policies |
4 |
24 |
- |
|
Python: data processing and analysis |
4 |
- |
30 CTD |
|
Environment and the challenges of ecological transition |
3 |
20 |
- |
|
English 4 |
2 |
- |
20 CTD |
|
IT core curriculum |
|
|
|
|
Algorithms and combinatorics of discrete structures |
10 |
24 |
10 TD 10 TP |
|
Application analysis and design |
9 |
16 |
16 TD 16 TP |
|
Dual degree courses |
|
|
|
|
Introduction to Machine Learning |
9 |
20 |
20 TD 10 TP |
|
Machine Learning project |
2 |
- |
- |
|
Internship (optional) |
- |
- |
- |
|
Trade conferences |
- |
- |
- |
|
3rd year |
|
|
|
|
Semester 5 |
|
|
|
|
Economics core curriculum |
|
|
|
|
Market Finance |
4 |
24 |
- |
|
Statistics applied to the economy |
4 |
24 |
15 TD |
|
Linear econometrics |
7 |
30 |
15 TD |
|
English 5 |
2 |
- |
15 TD |
|
PPP |
2 |
- |
- |
|
IT core curriculum |
|
|
|
|
Advanced programming |
8 |
15 |
30 TP |
|
Framework web 1 |
4 |
9 |
20 TP |
|
Information system |
7 |
15 |
20 TD 10 TP |
|
Communication techniques |
- |
- |
20 TD |
|
Dual degree courses |
|
|
|
|
Deep Learning |
9 |
- |
20 CTD 10 TP |
|
ML Project |
2 |
- |
- |
|
Semester 6 |
|
|
|
|
Economics core curriculum |
|
|
|
|
Advanced linear econometrics |
5 |
30 |
15 TD |
|
In-depth statistics |
5 |
30 |
15 TD |
|
Financial mathematics |
4 |
24 |
15 TD |
|
English 6 |
2 |
- |
15 TD |
|
IT core curriculum |
|
|
|
|
Framework web 2 |
4 |
18 |
20 TP |
|
n-tier programming |
5 |
18 |
30 TP |
|
Advanced algorithms |
5 |
8 |
16 TD 6 TP |
|
Web project |
2 |
- |
- |
|
Dual degree courses |
|
|
|
|
Machine Learning for business |
5 |
- |
25 CTD |
|
NLP |
9 |
- |
20 CTD 10 TP |
|
Internship (optional) |
- |
- |
- |
|
Trade conferences |
- |
- |
- |
Admission
Admission requirements
Hold a baccalaureate (preferably general) (see Parcoursup expectations)
Licence application procedures for (future) baccalaureate holders with a French baccalaureate obtained in France and applying for the 1st time: https: //www.parcoursup.fr
To be eligible for this course, it is essential to have taken the mathematics specialization in the final year of high school, with excellent results. Without being a prerequisite, the expert mathematics option, the NSI or SES specialties are definite advantages.
How to register
Enrolment in JULY, as soon as the results of the baccalauréat are known, in accordance with the procedures communicated at the time of pre-registration.
Tuition fees
For students:
https://www.univ-orleans.fr/fr/univ/formation/droits-dinscriptions
For adults returning to school; consult SEFCO.
Mandatory prerequisites
NATIONAL FRAMEWORK
And then
Further studies
The dual degree in Artificial Intelligence: Data and Organizational Sciences, for example, leads to the ÉSA (Applied Econometrics and Statistics) Master's degree and the MIAGE (Applied Computer Methods for Business Management) Master's degree at the University of Orléans. These master's programs are widely recognized in the professional world, thanks to long-standing partnerships with regional, national and international companies. They are supported by two research laboratories: the Laboratoire d'Économie d'Orléans and the Laboratoire d'Informatique Fondamentale d'Orléans. Their teaching and research staff have extensive experience in high-level training in their respective fields. Further studies may be envisaged in any other master's degree or school in the fields ofIT,economics, management or administration, at national or international level.
ESA Master website (external)
MIAGE master's website (external)
Professional integration
The multi-disciplinary nature of this course means that it offers a wide range of career opportunities. They encompass all professions that design and use IT, statistical and artificial intelligence tools to process data for decision-making in organizations. This includes, but is not limited to, jobs such as data analyst, data scientist, quantitative economist, e-business consultant, ERP consultant, business analyst, R&D engineer, IT project manager, software/IS architect, IT or econometrics researcher...".