Study programme 2022-2023Français
Multimedia Retrieval and Cloud Computing
Programme component of Master's in Computer Engineering and Management (MONS) (day schedule) à la Faculty of Engineering

CodeTypeHead of UE Department’s
contact details
Teacher(s)
UI-M2-IRIGIG-306-MOptional UEMAHMOUDI SidiF114 - Informatique, Logiciel et Intelligence artificielle
  • MAHMOUDI Saïd
  • MAHMOUDI Sidi

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Anglais
Anglais303000055.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-ILIA-014Machine & Deep Learning for Multimedia Retrieval1818000Q160.00%
I-ILIA-208Cloud and Edge Computing1212000Q140.00%

Programme component

Objectives of Programme's Learning Outcomes

  • Imagine, design, develop, and implement conceptual models and computer solutions to address complex problems including decision-making, optimisation, management and production as part of a business innovation approach by integrating changing needs, contexts and issues (technical, economic, societal, ethical and environmental).
    • Identify complex problems to be solved and develop the specifications with the client by integrating needs, contexts and issues (technical, economic, societal, ethical and environmental).
    • On the basis of modelling, design a system or a strategy addressing the problem raised; evaluate them in light of various parameters of the specifications.
    • Deliver a solution selected in the form of diagrams, graphs, prototypes, software and/or digital models.
    • Evaluate the approach and results for their adaptation (modularity, optimisation, quality, robustness, reliability, upgradeability, etc.).
  • Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out computer and management engineering missions, using their expertise and adaptability.
    • Master and appropriately mobilise knowledge, models, methods and techniques specific to computer management engineering.
    • Analyse and model an innovative IT solution or a business strategy by critically selecting theories and methodological approaches (modelling, optimisation, algorithms, calculations), and taking into account multidisciplinary aspects.
    • Identify and discuss possible applications of new and emerging technologies in the field of information technology and sciences and quantifying and qualifying business management.
  • Plan, manage and lead projects in view of their objectives, resources and constraints, ensuring the quality of activities and deliverables.
    • Define and align the project in view of its objectives, resources and constraints.
    • Exploit project management principles and tools, particularly the work plan, schedule, document monitoring, versioning and software development methodologies.
    • Assess the approach and achievements, regulate them in view of the observations and feedback received.
  • Work effectively in teams, develop leadership, and make decisions in multidisciplinary, multicultural and international contexts.
    • Interact effectively with others to carry out common projects in various contexts (multidisciplinary, multicultural, and international).
    • Contribute to the management and coordination of a team that may be composed of people of different levels and disciplines.
  • Communicate and exchange information in a structured way - orally, graphically and in writing, in French and in one or more other languages - scientifically, culturally, technically and interpersonally, by adapting to the intended purpose and the relevant public.
    • Argue to and persuade customers, teachers and boards, both orally and in writing.
    • Select and use the written and oral communication methods and materials adapted to the intended purpose and the relevant public.
  • Adopt a professional and responsible approach, showing an open and critical mind in an independent professional development process.
    • Analyse their personal functioning and adapt their professional attitudes.
    • Finalise a realistic career plan in line with the realities in the field and their profile (aspirations, strengths, weaknesses, etc.).
  • Contribute by researching the innovative solution of a problem in engineering sciences.
    • Construct a theoretical or conceptual reference framework, formulate innovative solutions from the analysis of scientific literature, particularly in new or emerging disciplines.
    • Develop and implement conceptual analysis, numerical modelling, software implementations, experimental studies and behavioural analysis.
    • Collect and analyse data rigorously.
    • Adequately interpret results taking into account the reference framework within which the research was developed.
    • Communicate, in writing and orally, on the approach and its results in highlighting both the scientific criteria of the research conducted and the theoretical and technical innovation potential, as well as possible non-technical issues.

Learning Outcomes of UE

Machine and Deep Learning for Multimedia Retrieval:
At the end of this teaching unit, the student would be able to:
- develop methods for searching, navigation and indexing multimedia databases;
- exploit deep learning techniques for searching and indexing multimedia databases.

Cloud and Edge Computing:
At the end of this learning activity, the student will be able to:
- Manage and manipulate Cloud and Edge architectures;
- Manage the basic concepts in the field of cloud computing: SaaS, PaaS, IaaS;
- Analyze efficiently the offers of cloud providers;
- Manage the tools of applications deployment and migration in the cloud/edge.
 

UE Content: description and pedagogical relevance

Content AA "Machine and Deep Learning for Multimedia Retrieval":
                                                        +
                    Content AA "Cloud and Edge Computing"

 

Prior Experience

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
I-ILIA-014
  • Cours magistraux
  • Conférences
  • Travaux pratiques
  • Travaux de laboratoire
  • Projet sur ordinateur
I-ILIA-208
  • Cours magistraux
  • Conférences
  • Travaux pratiques
  • Projet sur ordinateur

Mode of delivery

AAMode of delivery
I-ILIA-014
  • Face-to-face
I-ILIA-208
  • Face-to-face

Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-ILIA-014Not applicable
I-ILIA-208Not applicable

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-ILIA-014Not applicable
I-ILIA-208Not applicable

Other Recommended Reading

AAOther Recommended Reading
I-ILIA-014Not applicable
I-ILIA-208Not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
I-ILIA-014Authorized
I-ILIA-208Authorized

Term 1 Assessment - type

AAType(s) and mode(s) of Q1 assessment
I-ILIA-014
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face
I-ILIA-208
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face

Term 1 Assessment - comments

AATerm 1 Assessment - comments
I-ILIA-014Project evaluated within report and presentation
Practical test evaluated within program quality and performance
Project of the UE englobing the two AA "Machine and Deep Learning for Multimedia Retrival" and "Cloud and Edge Computing" 
I-ILIA-208Oral presentation of a project applying technologies seen in courses and labs (virtualisation, conterisation, deployment, etc.) on a concrete use case example in relation with the course of "Multimedia Retrieval"
Project of the UE englobing the two AA "Multimedia Retrival" and "Cloud and Edge Computing" 

Resit Assessment - Term 1 (B1BA1) - type

AAType(s) and mode(s) of Q1 resit assessment (BAB1)
I-ILIA-014
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face
I-ILIA-208
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face

Term 3 Assessment - type

AAType(s) and mode(s) of Q3 assessment
I-ILIA-014
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face
I-ILIA-208
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face

Term 3 Assessment - comments

AATerm 3 Assessment - comments
I-ILIA-014Idem Q1
I-ILIA-208Idem Q1
(*) 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
Date de dernière mise à jour de la fiche ECTS par l'enseignant : 15/05/2022
Date de dernière génération automatique de la page : 21/06/2023
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Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be