Explores boolean types, logical operators, and control structures in Python, emphasizing the evaluation of expressions and the use of relational operators.
Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.
Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.
Covers common operations on sequences like lists and tuples, including slicing, extending, and replacing elements.
Introduces functions in Python, covering predefined and user-defined functions, formal and effective parameters, and the importance of docstrings.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Covers Python sets operations, including creation, modification, and comparison, as well as set operations like union and intersection.
Covers operations and methods related to dictionaries in Python, including creating, updating, and handling key errors.
Covers rhythm generation techniques, including Markov models and hierarchical rhythm generation, with a focus on Nancarrow's Study 14.
