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.
or insert a code in a standard block; the code makes it possible to better filter the courses to be displayed: by sciper, unit, group, progcode (doctoral program code: EDAR, EDMA, etc.), section, orientation, semester, course, detail, format
In the right column, make sure the Block tab is active, if not, click on it.
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
You can then filter the information obtained using the drop-down menus in the Filters section.
Examples
LAPIS unit courses
Architecture section courses | Language : English | Orientation Master
With code, in a Standard block
Add a Classic Paragraph block (text)
Type this , as is, including the [ ] , in a text block
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
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.
Doctoral Program in Learning Sciences Teachers: Gatica-Perez Daniel Language: english Academic term: 2024-2025
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
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
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
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: Anjos André, Canévet Olivier, Marcel Sébastien Language: english Academic term: 2024-2025
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.
Doctoral Program in Computational and Quantitative Biology Teachers: Rougemont Jacques, Luisier Raphaelle, Bitbol Anne-Florence Raphaëlle Language: english Academic term: 2024-2025
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: Liebling Michael Stefan Daniel, Unser Michaël, Sage Daniel, Van De Ville Dimitri Nestor Alice Language: english Academic term: 2024-2025
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: Villamizar Michael, Calinon Sylvain, Odobez Jean-Marc, Canévet Olivier Language: english Academic term: 2024-2025
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
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 Civil Engineering Teachers: Stojilovic Mirjana, Lévêque Olivier Language: french Academic term: 2024-2025
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
