Courses

It is possible to automatically display on a page, a list of courses, for example of a lab or a person. Since this data is automatically extracted from is-academia, it is not necessary to update it with each change.

You can:

With the EPFL Courses block

  1. Add an EPFL Courses block.
  2. In the right column, make sure the Block tab is active, if not, click on it.
  3. In the Select by section, determine if you want to display the courses
    • By Unit. 
      Insert the acronym of the desired unit.
    • By teacher 
      If you want to display the courses of several teachers, enter their numbers separated by a comma without spaces.
      Example: 123456,123457,123458
    • By section
      Choose the section from the drop-down menu
  4. You can then filter the information obtained using the drop-down menus in the Filters section.

Examples

With code, in a Standard block

  1. Add a Classic Paragraph block (text)
  2. Type this , as is, including the [ ] , in a text block

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

Available settings

  • scipers | unit | groups | progcode : comma separated list
  • section : filter by section
  • orient : filter by orientation
  • sem : ete | hiver : filter by semester
  • 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, speaker recognition).

    Section of Digital Humanities
    Teachers: Magimai Doss Mathew
    Language: english
    Academic term: 2024-2025

  • 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 Twitter, Instagram, YouTube, and TikTok. Students will learn computational methods to understand phenomena in social media.

    MINEUR
    Teachers: Gatica-Perez Daniel
    Language: english
    Academic term: 2024-2025

  • 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: 2024-2025

  • Deep learning

    This course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.

    Doctoral Program in Learning Sciences
    Teachers: Cavallaro Andrea
    Language: english
    Academic term: 2024-2025

  • 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: Magimai Doss Mathew, Motlicek Petr
    Language: english
    Academic term: 2024-2025

  • Fundamentals in statistical pattern recognition



    Doctoral Program in Computational and Quantitative Biology
    Teachers: Canévet Olivier, Anjos André, Marcel Sébastien
    Language: english
    Academic term: 2024-2025

  • 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: 2024-2025

  • Genomics and bioinformatics

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

    Section of Life Sciences Engineering
    Teachers: Bitbol Anne-Florence Raphaëlle, Luisier Raphaelle, Rougemont Jacques
    Language: english
    Academic term: 2024-2025

  • Machine Learning for Engineers



    Doctoral Program in Microsystems and Microelectronics
    Teachers: Calinon Sylvain, Villamizar Michael, Odobez Jean-Marc, Canévet Olivier
    Language: english
    Academic term: 2024-2025

  • 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: 2024-2025

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

    Lévêque Olivier

    • Information, Computation, Communication

      The course objectives are to introduce the students to algorithmic thinking, to get them familiar with the foundations of communication and computer sciences and to develop a first set of skills in programming with the Python language.

      Section of Materials Science and Engineering
      Teachers: Lévêque Olivier, Stojilovic Mirjana
      Language: french
      Academic term: 2024-2025

    • 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.

      Quantum Science and Engineering Section
      Teachers: Lévêque Olivier, Urbanke Rüdiger
      Language: english
      Academic term: 2024-2025

    • Turing course, Cryptography



      HPLANS
      Teachers: Lévêque Olivier
      Language: english
      Academic term: 2024-2025