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-M2-INFOFS-006-MCompulsory UEGOSSELIN BernardF105 - Théorie des circuits et Traitement du signal
    Language
    of instruction
    Language
    of assessment
    HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
      Anglais0000044
      AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term
      I-TCTS-005
      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.
      • Manage research, development and innovation.
        • Understand unprecedented problems in computer science and its applications.
        • Methodically research valid scientific information, lead a critical analysis, propose and argue potentially innovative solutions to targeted problems.
      • Master communication techniques.
        • Where possible, communicate in a foreign language.
      • Develop and integrate a high degree of autonomy.
        • Pursue further training and develop new skills independently.
      • Apply scientific methodology.
        • Critically reflect on the impact of IT in general, and on the contribution to projects.
      • Skill 2: Have acquired professional skills in relation to the objective defining the degree.
        • Specialise in at least one sub-domain of computer science.
        • Integrate into a professional environment and collaborate with stakeholders on a project.

      UE's Learning outcomes

      develop an applied pattern recognition system, together with a critical analysis of the problem;
      apply data processing techniques (feature extraction, feature selection);
      apply classification techniques and train classifiers (Gaussian modelling, Clustering, Artificial Neural Networks, Support Vector Machines, Dynamic Time Warping, Hidden Markov Models, Combining Classifiers);
      estimate performances of classifiers.

      UE Content

      fundamentals: SPR scheme, feature extraction, classifiers, combining classifiers; neural networks: feed-forward neural networks, training MLP, other ANN models; support vector machines; dynamic systems: dynamic time warping, hidden Markov models; Speech Processing and Recognition

      Prior experience

      fundamentals of signal processing; probability and statistics

      Term 1 for Integrated Assessment - type

      • N/A

      Term 1 for Integrated Assessment - comments

      Not applicable

      Term 2 for Integrated Assessment - type

      • Oral Examination

      Term 2 for Integrated Assessment - comments

      Not applicable

      Term 3 for Integrated Assessment - type

      • Oral examination

      Term 3 for Integrated Assessment - comments

      Not applicable

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

      • N/A

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

      Not applicable

      Type of Teaching Activity/Activities

      AA
      I-TCTS-005

      Mode of delivery

      AA
      I-TCTS-005

      Required Reading

      AA
      I-TCTS-005

      Required Learning Resources/Tools

      AA
      I-TCTS-005

      Recommended Reading

      AA
      I-TCTS-005

      Recommended Learning Resources/Tools

      AA
      I-TCTS-005

      Other Recommended Reading

      AA
      I-TCTS-005
      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)