CS-423: Distributed information systemsThis course introduces the foundations of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems. ...
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and implement methods to analyze diverse data types, such as imag ...
CS-503: Visual intelligenceThis course covers both classic concepts and recent advances in computer vision and machine learning for processing visual data -- with a primary focus on embodied intelligence and multimodal learning ...
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...
CS-442: Computer visionComputer Vision aims at modeling the world from digital images acquired using video or infrared cameras, and other imaging sensors.
We will focus on images acquired using digital cameras. We will introduce basic processing techniques and discuss their fie ...
MICRO-511: Image processing IIntroduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping using Jupyter notebooks. Application to real-world examples in industrial vision and biomedical imaging. ...
CS-413: Computational photographyThe students will gain the theoretical knowledge in computational photography, which allows recording and processing a richer visual experience than traditional digital imaging. They will also execute practical group projects to develop their own computati ...
BIO-410: Bioimage informaticsThe course provides a comprehensive overview of methods, algorithms, and computer tools used in bioimage analysis. It exposes fundamental concepts and practical computer solutions to extract quantitative information from multidimensional images, both using ...
MICRO-512: Image processing IIStudy 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. ...
MSE-352: Introduction à la microscopie + TPCe cours d'introduction à la microscopie a pour but de donner un apperçu des différentes techniques d'analyse de la microstructure et de la composition des matériaux, en particulier celles liées aux microscopies électronique et optique. Le cours comprend d ...
EE-805: Fundamentals of Image AnalysisThis summer school is an hands-on introduction on the fundamentals of image analysis for scientists. A series of lectures provide students with the key concepts in the field, and are followed by practical sessions with popular software on the participants' ...
CIVIL-226: Introduction to machine learning for engineersMachine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinking education at EPFL, Civil students will learn ML with ...
DH-405: Foundations of digital humanitiesThis course introduces the core concepts and methodologies of Digital Humanities, integrating both theoretical and practical perspectives. Students learn to work with large-scale cultural datasets, acquiring the tools and techniques required for their proc ...
CIVIL-459: Deep learning for autonomous vehiclesDeep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects, make predictions, and make decisions. (Fun fact: this s ...
CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...
EE-559: Deep learningThis 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. ...
MICRO-452: Basics of mobile roboticsThis course gives an overview of the field of mobile robotics, introducing to the main techniques and allowing to test them in exercises and a team-based project. ...
AR-329: Constructing the view: built imagesWhat is meant by the term "image" as pictorial representation? How do we read, process and interpret images - and what premises can be derived from this for the conception and production of meaningful images? ...
