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Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Delves into advanced Spark optimization techniques, emphasizing data partitioning, shuffle operations, and memory management.
Covers rhythm generation techniques, including Markov models and hierarchical rhythm generation, with a focus on Nancarrow's Study 14.
Introduces a project where students teach robots to walk using reinforcement learning algorithms.
