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.) ...
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 ...
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.
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 ...
ME-301: Measurement techniquesTheoretical and practical course on experimental techniques for observation and measurement of physical variables such as force, strain, temperature, flow velocity, structural deformation and vibrations, etc. ...
EE-733: Design and Optimization of Internet-of-Things SystemsThis course provides a complete overview of the most relevant subfields related to Internet of Things (IoT) systems, it presents the perspectives and the underlying technologies, with a particular focus on edge AI architectures and software (AI and TinyML ...
FIN-525: Financial big dataThe course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to financial analysis, in particular to intraday data and inv ...
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 ...
PENS-227: Nuit à LausanneCe cours abordera la nuit à Lausanne sous une approche interdisciplinaire. À travers une traversée nocturne, nous dresserons un état des lieux des nuits lausannoises. La semaine permettra de réfléchir collectivement à des pistes pour l'avenir des nuits à L ...
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. ...
COM-621: Advanced Topics in Information TheoryThe class will focus on information-theoretic progress of the last decade. Topics include: Network Information Theory ; Information Measures: definitions, properties, and applications to probabilistic models. ...
BIO-603(LG): Practical - LaManno LabGive students a feel for how single-cell genomics datasets are analyzed from raw data to data interpretation. Different steps of the analysis will be demonstrated and the most common statistical and bioinformatic techniques applied by the students. Data an ...
MGT-644: Conducting Qualitative ResearchThis workshop will expose you to a combination of readings, discussions, and hands-on exercises aimed at cementing your
understanding of, and ability to conduct qualitative research - especially gathering, analyzing, and theorizing different types of
quali ...
ME-412: Experimental methods in engineering mechanicsThis course gives an advanced treatment of experimental methods in the context of mechanics by way of example. Students will construct significant components of experimental apparatus, use their apparatus to collect data, interpret the resulting data, and ...
FIN-604: Financial Econometrics IWe provide a comprehensive overview of the econometric tools that are essential to estimate financial models, both for asset pricing and
for corporate finance. ...
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 ...
