Python for Data Science and ML

Write basic Python scripts using variables, control flow (if/else, for/while loops), and function definitions

Write Python functions using list comprehensions, generators, and decorators

Implement a class hierarchy with inheritance and dunder methods in an ML context (e.g., a model base class with fit and predict methods)

Perform vectorized array operations and broadcasting using NumPy

Select, filter, and modify data within Pandas DataFrames using indexing and boolean masking

Create publication-quality plots using Matplotlib and Seaborn

Preprocess data for ML: handle missing values, encode categorical features, and apply feature scaling using scikit-learn