Advanced Pandas Functions

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Page 3 of 4

Introduces Vectorworks Educational Version for architectural drawings, covering tools, layers, and annotations.

Explores tools like Git and Docker for collaborative data science projects.

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.

Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.

Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.

Delves into advanced Spark optimization techniques, emphasizing data partitioning, shuffle operations, and memory management.

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Covers rhythm generation techniques, including Markov models and hierarchical rhythm generation, with a focus on Nancarrow's Study 14.