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Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
Explores boolean types, logical operators, and control structures in Python, emphasizing the evaluation of expressions and the use of relational operators.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
Explores sources of unfairness in machine learning, the importance of fairness metrics, and evaluating model predictions using various fairness metrics.