Covers the fundamentals of database systems, including data modeling, information processing, and the challenges of managing large volumes of data.
Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.
Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.
Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.
Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.
Explores deanonymization using public datasets from Netflix, focusing on matching users and evaluating films based on ratings.
Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
