Data Analysis Replication & Creative Extension

Related lectures (31)

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Outlines the master's programs in Statistics and Microengineering at EPFL, detailing their structure, courses, and career opportunities.

Explores EPFL's doctoral theses history, data visualization, and the innovative D3 approach.

Introduces the course 'How People Learn II', focusing on educational concepts and practical applications in project-based learning.

Explores data manipulation, exploration, and visualization in data science projects using Python.

Covers machine learning approaches for personalization and their real-world application, emphasizing homework, projects, and feedback.

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

Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.

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.

Covers project management methodologies, network calculation, resource allocation, and monitoring-control in project planning and scheduling.

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.