Study programme 2015 - 2016
Programme component of Master's Degree in Computer Science à la Faculty of Science
CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCINFO-016-MCompulsory UEDUMONT MartineM184 - Biomathématiques
    Language
    of instruction
    Language
    of assessment
    HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
      Français0000022
      AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term
      S-MATH-069
      Integrated Assessment: There will be an overall assessment for the entire Programme component (UE) instead of individual assessments for each Teaching Activity (AA)

      Objectives of general skills

      • 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.

      UE's Learning outcomes

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

      UE Content

      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

      Term 1 for Integrated Assessment - comments

      Not applicable

      Term 2 for Integrated Assessment - type

      • Presentation and works

      Term 2 for Integrated Assessment - comments

      Not applicable

      Term 3 for Integrated Assessment - type

      • Presentation and works

      Term 3 for Integrated Assessment - comments

      Not applicable

      Resit Assessment for IT - Term 1 (B1BA1) - Comments

      Not applicable

      Type of Teaching Activity/Activities

      AA
      S-MATH-069

      Mode of delivery

      AA
      S-MATH-069

      Required Reading

      AA
      S-MATH-069

      Required Learning Resources/Tools

      AA
      S-MATH-069

      Recommended Reading

      AA
      S-MATH-069

      Recommended Learning Resources/Tools

      AA
      S-MATH-069

      Other Recommended Reading

      AA
      S-MATH-069
      UE : Programme component - AA : Teaching activity
      (*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
      Integrated Assessment: There will be an overall assessment for the entire Programme component (UE) instead of individual assessments for each Teaching Activity (AA)