Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
Covers the recap of forced and free convection, including the definition of convection and the general procedure to determine the convection coefficient.
Explores forced external convection correlations and the procedure for solving convection problems, including the comparison of velocity and thermal boundary layers.
