Core Python and Applied Integration

This unit develops essential Python programming skills—control flow, data types, functions, classes, file I/O, error handling, and package use—while introducing applied workflows in data science, machine learning, and Raspberry Pi hardware integration. Students will practice writing, documenting, debugging, organizing, and serializing code to prepare for more advanced AI and robotics projects.

Learning Objectives

• Analyze and implement Python control flow and data structures by writing programs that use conditionals, for loops, tuples, sets, and dictionaries to solve specified problems.
• Apply modular and object-oriented programming practices by creating functions with clear comments, designing classes, instantiating objects, and organizing code into packages and modules.
• Demonstrate robust input/output and maintenance techniques by reading from and writing to files, using serialization formats (e.g., JSON/pickle), and implementing try/except error handling and debugging workflows.
• Evaluate and apply introductory data science, machine learning, and hardware integration concepts by building a simple ML model, articulating AI limitations, and controlling Raspberry Pi sensors and actuators from Python.