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Online Exchange Initiative (OEI) - ENGAGE.EU - Etudiants entrants - S2

Les étudiants des universités partenaires d'ENGAGE.EU peuvent participer à un échange virtuel à l'Université Toulouse Capitole au 2nd semestre 2021/22.


Photo - Logo Engage.eu
L'Université Toulouse Capitole et l'ensemble des partenaires de l'alliance ENGAGE.EU (LUISS University, NHH Norwegian School of Economics, Tilburg University, University of Mannheim, University of National and World Economy, WU Vienna), ont lancé une initiative d'échange en ligne (Online Exchange Initiative). Les étudiants des établissements mentionnés ci-dessus peuvent présenter une candidature pour participer aux cours offerts par UT Capitole. En tant que participant, vous serez étudiant dans une classe virtuelle internationale. Profitez des avantages d'étudier dans un contexte international !

Ma candidature

Qui peut participer ?

Les cours en ligne sont ouverts aux étudiants des établissements indiqués ci-dessous :
  • LUISS University
  • NHH Norwegian School of Economics
  • Tilburg University
  • University of Mannheim
  • University of National and World Economy
  • WU Vienna

Période de candidature

Les candidatures sont désormais fermées.

Comment présenter ma candidature ?

La sélection se fera sur la base de vos résultats et de votre motivation à intégrer le cours. Les candidatures sont fermées pour le 2nd semestre 2021/22.

Relevé de notes

A la fin de votre échange à distance, vous recevrez une relevé de notes officiel de l'Université Toulouse Capitole. Rapprochez-vous de votre établissement d'origine pour le transfert des crédits obtenus.

Catalogue de cours de l'Université Toulouse Capitole

Période de candidature : du 29 novembre au 13 décembre 2021
Période de cours : du 3 janvier au 1er avril 2022
Examens : avril 2022

Droit - Niveau Master

Company Law

ECTS : 2
Language of instruction : English
Attendance: Online or in class
Hours: 15
Description: This course aims at equipping attendees with basic notions on companies and comparative insights.
As major economic players, companies face key challenges and crucial legal issues: protection of founders, governance rules, role played by employees, financing.
This company law course focuses on French and EU law.
Teaching method involves practical case studies
 

E-commerce Law

ECTS : 2
Language of instruction : English
Attendance: Online or in class
Hours: 15
Description: E-commerce European legal framework including notion of e-commerce, the main actors involved and their liability. A focus will be done on data protection law and e-sport law.
 

Internal Market

ECTS : 5
Language of instruction : English
Attendance: Online or in class
Hours: 30
Description: Internal Market-the class aims at giving students a broader knowledge on the substantive aspects of European Law, with a focus on the four economic freedoms shaping the continuous development of the internal market. Teaching method involves the analysis of jurisprudence and practical cases.

Management - Niveau Bachelor

Quantitative Methods

ECTS : 3
Language of instruction : English
Attendance: Online
Hours and schedule: 15h - Tuesdays from 4pm to 5.30pm (from January 10th to March 22nd)
Description: This course presents basic statistical thinking and data analysis techniques for decision-making under uncertainty, as applied in management and economics. It does not dwell on the details of computation, its main focus is on understanding a few statistical concepts and methods for interpreting data. It includes computer analysis of data.
By the end of the course, students should be able to produce and interpret graphical displays and numerical summaries of data, perform basic statistical hypothesis testing as well as simple regression analysis.
Prerequisites: Basic probability theory. Classical discrete and continuous distributions.

Information technology - Niveau Master

Artificial Intelligence

ECTS : 5
Language of instruction : English
Attendance: Online or in class
Hours and Schedule: 39h - Mondays from 2pm to 5pm (from January 3rd to April 11)
Description: The course is structured in two parts.
1. Machine learning: building on the “Data Analytics” course proposed in the first
semester, students will learn the basics of supervised machine learning such as
SVM, linear classifiers, deep learning, and bayesian inference. At the same time,
students will be asked to complete a group project in 5 weeks, selecting one of the
techniques presented during the course and implementing it (typical example: a
classification problem).
2. Reasoning: the second part of the course will cover classical AI techniques such as
exploration and search algorithms, game playing, and constraint satisfaction. A set
of exercises to be solved individually on paper will be proposed, as well as a
second project based on modeling and solving a constraint satisfaction problem,
with the objective of winning the end-of-course tournament.
Each part of the course lasts for 6 weeks, with the first 2 weeks dedicated to lectures by
the teachers, and the remaining weeks consisting of tutoring sessions in the lab and
student presentations. These two aspects are completed with an introductory session on
AI in the form of a world coffee and two lectures on the history and ethics in AI.
Prerequisites: The courses of Advanced Programming and Data Analytics in semester 1.

Web services

ECTS : 5
Language of instruction : English
Attendance: Online or in class
Hours and Schedule: 39h - Wednesdays from 2pm to 5pm (from January 12th to March 30th)
Description: Web services are now a mature technology to organize an Information System and make
available the content of a database with a given API, allowing users to build their own
application on top of this data. This course objective is to let student build a project where
they can build an application able to consume external web services (thus access data from
external web services), and build a webservice to provide new data.
Prerequisites: Advanced skills in Java programming, and basic knowledge of the internet are necessary.
Prerequisites: Advanced Programming class.