Teacher(s)
Language
French
Learning outcomes
At the end of this learning unit, the student is able to : | |
| Competency 2 - Know and orchestrate the technical, creative and marketing aspects of digital projects in organisational communication. Learning Outcomes : 1. Know the main principles of the architecture, operation and security of computer networks and social network technologies of an organisation, as well as the main computer technologies. 3. Know the characteristics, opportunities and constraints of the different digital channels; integrate them in a logical way in a communication plan. 4. Know the techniques and methods for optimising the referencing, reputation and running of online communities. 6. Combine 'online' and 'offline' communication modes in any communication strategy in an optimal manner. Competency 3 - Develop a digital culture for the organisation which mobilises management, teams and partners in communication strategies and projects. Learning Outcomes : 1. Advise the organisation's decision-making bodies on the challenges and issues at the crossroads of communication and digital innovations (communication objectives and strategies, communication as a managerial lever, the organisation's digital transformation, etc.). Competency 4 - Mobilise and produce knowledge in communication strategy and digital culture in a substantiated and methodical manner, as part of a critical reflection or research project. Learning Outcomes : 2. Based on multidisciplinary knowledge, develop a critical and substantiated reflection on digital technologies and their human and societal issues. 6. Update one’s knowledge and practices by implementing methods and techniques to monitor communication and digital trends and innovations. |
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Content
The course covers four main topics: i) computer networks (sets of computers interconnected via wired or wireless links, transmitting information as digital data) and ii) information systems (the elements and components involved in the management, storage, processing, transport, exchange, and representation of information within an organization), as well as their implementation in the contexts of iii) digital social networks and iv) distributed artificial intelligence—specifically its application to networks of interconnected entities and objects (conversational agents, sensors, etc.).
The course presents and details these topics in order to provide
Part 0 : Introduction
The course presents and details these topics in order to provide
- the methodological and practical knowledge, supported by exercises, reading of articles and demonstrations, that are necessary for the understanding, the design and the management of an information system.
- the essential tools for specifying a communications strategy on digital social networks (private/public company, association, institution, etc.).
- the conceptual foundations for understanding and analyzing a technical document (journal article, expert report, specification, etc.) that presents a critical reasoning regarding the adoption or choice of a technology or application relevant to the course.
Part 0 : Introduction
- General presentation of information systems, their purposes and roles from the technical and socioeconomic points of views.
- Explore the concept of information system, its components and its types in order to analyze more precisely the mechanisms of exchange and transport of information by means of its network component.
- Components, functions/reference models (OSI, hour-glass) and main protocols (Ethernet, TCP/IP, HTTP, DNS)
- Types of networks: local (data centers, enterprise/industrial, etc.), access (radio/mobile/non-wired, wired access) and global/remote (Internet), and their interconnections (switch, router)
- Communication/operation mode: peer-to-peer, client-server (2-tier), gateway (3-tier, n-/multi-tier)
- Services and providers: Internet/connectivity, content, web service, cloud service (storage, computing, platform/container, etc.)
- Main functions: i) secure exchange (collection and distribution/dissemination) of information, ii) storage and processing of information and iii) management and security of information -and- technological solutions/alternatives
- Information coding, digital data and main data models : entity-association, entity-relation, graphical
- Introduction to big data and data mining (including unsupervised methods)
- Architecture of big data systems and platforms (including data storage/hosting and processing)
- Foundational and fundamental concepts, and evolution of the human-machine interface
- Critical presentation of key issues (socio-economic, cultural, institutional, security-related, etc.)
- Infrastructure, superstructure, and technological solutions
- Specifying a communication plan using digital social networks (private/public companies, associations, institutions, etc.)
- Concrete examples of developing and implementing a communication plan using digital social networks
- Foundational and fundamental concepts of distributed artificial intelligence
- Decentralization: networks of (semi-)autonomous agents
- Interfaces and interactions between the physical and digital worlds: sensors and actuators
- Infrastructure, superstructure, and technological solutions
- Case studies: from conversational agents to the Turing test; networks of interconnected objects (Internet of Things)
Teaching methods
Course : 15 modules of 3 hours
Teaching methods include:
Teaching methods include:
- Lecture (2 hours): presents the numerous architectural concepts, models and operating principles, technological alternatives/solutions, etc. while encouraging students to have as much interaction as possible.
- Practicum (1 hour): alternately, carrying out practical/formative exercises or reading/analyzing specialized articles and group discussions to understand the relationships between the concepts presented and anchor them in concrete terms students.
- NB : Student attendance at class sessions is required. These sessions are an integral part of the course material, featuring numerous supplementary points, examples, exercises, and further elaborations not detailed in the course handouts.
- the course material (slides);
- the various resources (articles, references, case studies, etc.) whose consultation is requested/ recommended;
- to the various tools used to illustrate the implementation of the different techniques presented in the course;
- self-evaluation tests (MCQ type).
Evaluation methods
- First session: first-session grade = 1.00 × written exam grade.
- Individual written exam (100%), closed-book. Use of AI is strictly prohibited. The exam covers all concepts previously communicated and taught via course materials.
- Second session: second-session grade = 1.00 × oral exam grade.
- Individual oral exam (100%), closed-book. Use of AI is strictly prohibited. The exam covers all concepts previously communicated and taught via course materials.
Bibliography
- Une bibliographie complète est intégrée au support de cours sur Moodle.
- Une bibliographie spécifique est mise a disposition en début de chaque partie du cours.
- A complete bibliography is integrated into the course material available on Moodle.
- A specific bibliography is made available at the start of each part of the course.
Faculty or entity