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.
• Lead a project by mastering its complexity and taking into account the objectives, allocated resources and constraints that characterise it.
• Demonstrate independence and their ability to work alone or in teams.
• Manage research, development and innovation.
• Methodically research valid scientific information, lead a critical analysis, propose and argue potentially innovative solutions to targeted problems.
• Master communication techniques.
• Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
• Develop and integrate a high degree of autonomy.
• Aquire new knowledge independently.
• Pursue further training and develop new skills independently.
• Apply scientific methodology.
• Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

Introduction to different methods of characterization of complex time series voir AA  S-Math-069

Content of UE

Introduction to some classical tools for time series characterization. Presentation of some non linear analysis tools for complex time series characterization: correlation dimension, Lyapunov exponents, Kolmogorov entropy, non linear prediction, generalyzed synchronization between several complex time series voir AA  S-Math-069

Prior Experience

Not applicable

Type of Assessment for UE in Q2

• Presentation and/or works

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

• Presentation and/or works

Q3 UE Assessment Comments

Not applicable