A two-part course that sharpens advanced Python skills and builds practical data-handling ability. The first part focuses on deeper Python concepts and performance-aware coding. The second part covers essential data processing with NumPy, pandas, basic plotting, and a minimal intro to ML workflows.

Part I — Advanced Python

• Object-oriented design: classes, inheritance, mixins

• Iterators, generators, decorators

• Algorithms and time complexity

• Common search/sort patterns

• Async programming with async/await

Part II — Data Science Tools

• NumPy: vectorization and array operations

• Pandas: indexing, filtering, grouping, merging

• Data cleaning and transformation

• Core plotting with Matplotlib/Seaborn

• Basic modeling flow with scikit-learn (train/test + simple models)