Objectives of Programme's Learning Outcomes

• Manage large-scale software development projects.
• Apply, mobilise, articulate and promote the knowledge and skills acquired in order to help lead and complete a project.
• Master communication techniques.
• Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
• Adapt their communication to a variety of audiences.
• Develop and integrate a high degree of autonomy.
• Aquire new knowledge independently.

Learning Outcomes of UE

At the end of the instruction, the students will be able to :
- Identify the multivariate analysis technique according to the nature of the statistical variables
- to apply the techniques of analysis in principal components, analysis of the (multiple) correspondences and the automatic classification in the statistical treatment of multidimensional sets of data
- to use a software of multidimensional statistical analysis

Content of UE

- Singular values decomposition
- Principal components analysis
- (Multiple) correspondence analysis
- Techniques of classification (k-means, hierachical clustering)
- Support vector machines

Prior Experience

- Uni- and bivariate basic statistics
- Hypothesis tests
- Basic matrix algebra

Type of Assessment for UE in Q2

• Presentation and/or works

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

• Oral examination

Q3 UE Assessment Comments

Not applicable