Courses (liste des cours)

Il est possible d’afficher automatiquement sur une page, une liste de cours, par exemple d’un labo ou d’une personne. Ces données étant extraites automatiquement de is-academia, il n’est pas nécessaire de les mettre à jour à chaque changement.

Vous pouvez:

Avec le bloc EPFL Courses

  1. Ajouter le bloc EPFL Courses…
  2. Dans la colonne de droite, assurez-vous que l’onglet Bloc est actif, si ce n’est pas le cas, cliquez dessus.
  3. Dans la section Sélection par, déterminez si vous souhaitez afficher les cours
    • Par Unité.
      Insérez l’acronyme de l’unité voulue
    • Par enseignant/e/s 
      Si vous souhaitez afficher les cours de plusieurs enseignants, entrez leurs numéros sciper séparés par une virgule sans espace
      Exemple : 123456,123457,123458
    • Par section
      Choisissez la section dans le menu déroulant
  4. Vous avez ensuite la possibilité de filtrer les informations obtenues en utilisant les menus déroulants de la section Filtres

Exemples

Avec le code, dans un bloc Standard

  1. Ajouter un bloc  Classic Paragraph (texte
  2. Taper ceci , tel quel, y compris les [ ] , dans un bloc texte

[remote_content url="https://people.epfl.ch/cgi-bin/getCours?unit=Votre_unité"]

Paramètres disponibles

  • scipers | unit | groups | progcode : liste séparée par des virgules
  • section : filtre par section
  • orient : filtre par orientation
  • sem : ete | hiver : filtre par semestre
  • cursus : ba | ma | phd
  • detail : L | M | S 
  • format : html | json 

Exemples

[remote_content url="https://people.epfl.ch/cgi-bin/getCours?unit=LIDIAP"]

  • Automatic speech processing

    The goal of this course is to provide the students with the main formalisms, models and algorithms required for the implementation of advanced speech processing applications (involving, among others, speech coding, speech analysis/synthesis, and speech recognition).

    Section of Digital Humanities
    Teachers: Magimai Doss Mathew
    Language: english
    Academic term: 2023-2024

  • Computational Social Media

    The course integrates concepts from media studies, machine learning, multimedia, and network science to characterize social practices and analyze content in platforms like Facebook, Twitter, and YouTube. Students will learn computational methods to understand phenomena in social media.

    Doctoral Program in Electrical Engineering
    Teachers: Gatica-Perez Daniel
    Language: english
    Academic term: 2023-2024

  • Deep Learning For Natural Language Processing

    The Deep Learning for NLP course provides an overview of neural network based methods applied to text. The focus is on models particularly suited to the properties of human language, such as categorical, unbounded, and structured representations, and very large input and output vocabularies.

    Doctoral Program in Electrical Engineering
    Teachers: Henderson James
    Language: english
    Academic term: 2023-2024

  • Deep learning

    The objective of this course is to provide a complete introduction to deep machine learning. How to design a neural network, how to train it, and what are the modern techniques that specifically handle very large networks.

    Doctoral Program in Electrical Engineering
    Teachers: Cavallaro Andrea
    Language: english
    Academic term: 2023-2024

  • Digital Speech and Audio Coding

    The goal of this course is to introduce the engineering students state-of-the-art speech and audio coding techniques with an emphasis on the integration of knowledge about sound production and auditory perception through signal processing techniques.

    Doctoral Program in Electrical Engineering
    Teachers: Motlicek Petr, Magimai Doss Mathew
    Language: english
    Academic term: 2023-2024

  • Fundamentals in statistical pattern recognition

    This course provides in-depth understanding of the most fundamental algorithms in statistical pattern recognition or machine learning (including Deep Learning) as well as concrete tools (as Python source code) to PhD students for their work.

    Doctoral Program in Electrical Engineering
    Teachers: Marcel Sébastien, Anjos André, Canévet Olivier
    Language: english
    Academic term: 2023-2024

  • Fundamentals of machine learning

    This course provides a general overview of machine learning, covering the main algorithms, theoretical formalisms, and experimental protocols.

    Section of Electrical and Electronical Engineering
    Teachers: Liebling Michael Stefan Daniel
    Language: french
    Academic term: 2023-2024

  • Genomics and bioinformatics

    This course covers various data analysis approaches associated with applications of DNA sequencing technologies, from genome sequencing to quantifying gene expression, transcription factor binding and chromosome conformation.

    Section of Mathematics
    Teachers: Rougemont Jacques, Luisier Raphaelle
    Language: english
    Academic term: 2023-2024

  • Image processing II

    Study of advanced image processing; mathematical imaging. Development of image-processing software and prototyping in Jupyter Notebooks; application to real-world examples in industrial vision and biomedical imaging.

    Doctoral program in robotics, control, and intelligent systems
    Teachers: Van De Ville Dimitri Nestor Alice, Liebling Michael Stefan Daniel, Unser Michaël, Sage Daniel
    Language: english
    Academic term: 2023-2024

  • Machine Learning for Engineers

    The objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice. Laboratories will be done in python using jupyter notebooks.

    Doctoral Program in Electrical Engineering
    Teachers: Odobez Jean-Marc, Villamizar Michael, Canévet Olivier, Calinon Sylvain
    Language: english
    Academic term: 2023-2024

  • Perception and learning from multimodal sensors

    The course will cover different aspects of multimodal processing (complementarity vs redundancy; alignment and synchrony; fusion), with an emphasis on the analysis of people, behaviors and interactions from multimodal sensor, using statistical models and deep learning as main modeling tools.

    Doctoral Program in Electrical Engineering
    Teachers: Odobez Jean-Marc
    Language: english
    Academic term: 2023-2024

    • [remote_content url="https://people.epfl.ch/cgi-bin/getCours?scipers=107931&lang=en&display=byprof"]

    Lévêque Olivier

    • Information, Computation, Communication

      On one side, this course covers the concepts of algorithms, the representation of information, signal sampling and compression, and an overview of systems (CPU, memory, etc.). On the other side, an introduction to programming in Python is given.

      Section of Chemistry and Chemical Engineering
      Teachers: Pellet Jean-Philippe, Lévêque Olivier
      Language: french
      Academic term: 2023-2024

    • Markov chains and algorithmic applications

      The study of random walks finds many applications in computer science and communications. The goal of the course is to get familiar with the theory of random walks, and to get an overview of some applications of this theory to problems of interest in communications, computer and network science.

      Section of Communication Systems
      Teachers: Macris Nicolas, Lévêque Olivier
      Language: english
      Academic term: 2023-2024

    • Introduction to quantum computation

      The course introduces the paradigm of quantum computation in an axiomatic way. We introduce the notion of quantum bit, gates, circuits and we treat the most important quantum algorithms. We also touch upon error correcting codes. This course is independent of COM-309.

      Section of Communication Systems
      Teachers: Urbanke Rüdiger, Lévêque Olivier
      Language: english
      Academic term: 2023-2024

    • Turing course, Cryptography



      HPLANS
      Teachers: Lévêque Olivier
      Language: english
      Academic term: 2023-2024