Cloud Computing

lingi2145  2020-2021  Louvain-la-Neuve

Cloud Computing
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h + 15.0 h
Riviere Etienne;
You would already have passed LINGI2172 Databases
Main themes
  • Architectural principles of cloud computing
  • Scalability of cloud services (storage, computing, ...)
  • Building blocks for cloud services
  • Large scale computations in cloud environments
  • Programming models for cloud services
  • Providing scalable web services from the cloud

At the end of this learning unit, the student is able to :

1 Given the learning outcomes of the "Master in Computer Science and Engineering" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • INFO1.1-3
  • INFO2.2-3, INFO2.5
  • INFO5.2, INFO5.4-5
  • INFO6.1, INFO6.3, INFO6.4
Given the learning outcomes of the "Master [120] in Computer Science" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
  • SINF1.M1
  • SINF2.2-3, SINF2.5
  • SINF5.2, SINF5.4-5
  • SINF6.1, SINF6.3, SINF6.4
Students having completed this course successfully will be able to
  • explain the goals, benefits and models of cloud computing, providing practical examples
  • describe the main components of cloud computing
  • design and conceive cloud services which operate reliably at scale
  • explain how storage and virtualization are used in the cloud and apply this in practice
  • apply the fundamental principles of multi-tier web applications and services in a cloud environment
  • tackle big data computation problems (e.g., through the Map Reduce computing paradigm)
This course focuses on the issues and programming models related to cloud computing environments and distributed data processing technologies: data partitioning, storage schemes, stream processing, and "mostly shared-nothing" parallel algorithms.
Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

  • Lectures
  • Scientific readings
  • Quizzes (about readings, labs and lectures)
  • Practical lab sessions
  • Project
Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The final grade is computed as follows for the first session (January): 
  • Project 45%
  • Final exam 45%
  • Online quiz and peer review of other students work 10%
It will not be possible to redo the project or the quizzes for the second session. However, the scale for the second session (September) is changed to:
  • Project 45%
  • Final exam 55%
Continuous evaluation initially proposed with formative evaluation only could be graded and account for all or a part of the grade devoted to the final exam, if dictated by circumstances.
The professor may request a student to go through an additional oral exam as a complement of the final exam and/or of the project, in cases including, but not limited to, technical issues, or suspicion of irregularities.
Other information
Background :
  • LINFO1341
  • LINFO1121
  • LINFO1252
Recommended background:
  • Computer networks
  • Have a good understanding of computational complexity
Faculty or entity
Force majeure
Evaluation methods
An alternative exam using an adapted modality will be simultaneously offered to students who can prove before the exam their impossibility to participate to the exam on site. This impossiblity must be attested, for instance with a quarantine certificate or a "formulaire retour" of the Foreign Affairs SPF. Students have the obligation to notify the professor at least 48 hours in advance of the exam if the quarantine situation started earlier than 48 hours before the exam. A student who would report a quarantine situation to the professor but who would not send her or his certificate to the EPL secretary within 24 hours after the end of the exam will see her or his alternative exam cancelled and ignored (i.e., she or he will be considered as not attending the exam on site). The alternative exam will be on the same material as covered by the main exam, and will take place under a form compatible with the quarantine situation of the student. All students who undergo an alternative exam will also be interrogated orally.

Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Master [120] in Data Science : Statistic

Master [120] in Computer Science and Engineering

Master [120] in Computer Science

Master [120] in Mathematical Engineering

Master [120] in Data Science Engineering

Master [120] in Data Science: Information Technology