What you'll learn

• Understand and use Python dictionaries
• Use dictionaries to store appropriate data
• Understand the CSV format and how it represents structured data.
• Read and parse CSV files.
• Convert CSV data into NumPy arrays and Pandas DataFrames
• Create and manipulate NumPy arrays for 1D and 2D datasets.
• Create various plot types using matplotlib.pyplot
• Learn how visualization complements statistical analysis to reveal trends in data
• Understand type abstraction and why it matters in Python programming.
• Create user-defined types with classes, attributes, and methods.
• Build modular code using classes to simulate real-world systems.
• Design simulations of real-life situations using data abstraction and object-oriented design.
• Learn different types of ML problems: classification, regression, and clustering.
• Study how decision trees and random forests work
• Understand overfitting and randomness in ensemble methods
• Apply learned Python skills to explore machine learning examples