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).
Section of Digital Humanities Teachers: Magimai Doss Mathew Language: english Academic term: 2023-2024
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
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
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
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
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, Canévet Olivier, Anjos André Language: english Academic term: 2023-2024
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.
MINEUR Teachers: Luisier Raphaelle, Rougemont Jacques Language: english Academic term: 2023-2024
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
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
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
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
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
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.
