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).

    Section of Computer Science
    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

    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 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: Magimai Doss Mathew, Motlicek Petr
    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: Bitbol Anne-Florence Raphaëlle, Rougemont Jacques, Luisier Raphaelle
    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 Environmental Sciences and Engineering
      Teachers: Lévêque Olivier, Pellet Jean-Philippe
      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 Computer Science
      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.

      MINEUR
      Teachers: Lévêque Olivier, Urbanke Rüdiger
      Language: english
      Academic term: 2023-2024

    • Turing course, Cryptography



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