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.) ...
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 ...
ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanical engineering applications. ...
ENV-370: Environmental system analysis and assessmentLes enjeux environnementaux doivent être abordés de façon systémique. L'Analyse du Cycle de Vie (ACV) et l'Analyse de Flux de Matière (AFM) sont des méthodes permettant d'évaluer de façon globale les performances environnementales des produits, des service ...
LEARN-610: Introduction to Methods in Learning Sciences 1This is part 1 of a two part course that provides students with knowledge and skills in collecting, processing and analyzing educational data, including different lenses to view the nature of inquiry in the field, research designs, and an overview of quant ...
COM-490: Large-scale data science for real-world dataThis hands-on course covers tools and methods used by data scientists, from researching solutions to scaling prototypes on Spark clusters. Students engage with the full data engineering and data science pipeline, from data acquisition to extracting insight ...
CS-421: Machine learning for behavioral dataComputer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will cover the core methods of user modeling and personalizatio ...
MSE-213: Probability and statistics for materials scienceThe course establishes the concepts of statistical analysis, probability theory, and data analysis. This includes standard statistical tests, correlation analysis and experimental design. It introduces computational statistical methods to analyse large dat ...
ENV-444: Exploratory data analysis in environmental healthThis course teaches how to apply exploratory spatial data analysis to health information. Teaching focuses on the role of GIS and spatial statistics in spatial epidemiology. It proposes a context to investigate the relationship between health, quality of l ...
EE-548: AudioThis lecture is oriented towards the study of audio engineering, room acoustics, sound propagation, and sound radiation from sources and acoustic antennas. The learning outcomes will be the techniques for microphones and loudspeaker design, as well as room ...
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
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-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. ...
MGT-448: Statistical inference and machine learningThis course aims to provide graduate students a thorough grounding in the methods, theory, mathematics and algorithms needed to do research and applications in machine learning. The course covers topics from machine learning, classical statistics, and data ...
CS-233(a): Introduction to machine learning (BA3)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
BIO-645: Introduction to Applied Data Science (I2ADS)The "Introduction to Applied Data Science" (I2ADS) course is aimed at students of all levels to train them in the core computer science software stack and techniques forming the pillars of open & reproducible science.
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HUM-485: Data in context: Critical Data Studies ILe cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématiques complexes qui nécessitent une méthodologie interdiscip ...
HUM-486: Data in context: Critical Data Studies IILe cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements UNIL/EPFL qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématiques complexes qui nécessitent une méthodologie interd ...
