Data Science and Education at EPFL

Related lectures (32)

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Covers unsupervised learning, focusing on dimensionality reduction and clustering, explaining how it helps find patterns in data without labels.

Introduces the Distributed Information Systems course, emphasizing key concepts and practical tools for data processing.

Introduces a course on Genetics & Genomics, focusing on R programming with interactive exercises.

Introduces the team, provides a crash course on Python, and explores the journey into Data Science and the importance of refining data.

Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.

Covers the fundamentals of data science, the scientific method evolution, the role of a data scientist, and the significance of data as the new oil.

Explores text mining, data curation, and brain connectivity in neuroscience.

Explores knowledge representation, data structures, semantics, and the challenges of searching for data on the web.

Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.