How karchun0910/ai works
This is a Week 2 Python-for-AI teaching repository, not an application: its main product is two student notebooks accompanied by sample datasets and environment setup materials. The documented workflow is to create and clone a GitHub template, configure Python in VS Code, install dependencies, verify the environment, and work through the notebooks. Notebook internals and dataset usage were not sampled, so no links between them are asserted.
Main entry points: Wk2a_Python_Rapid_Transition.ipynb Python transition · Wk2b_Data_Toolkit.ipynb Data toolkit · requirements.txt Package requirements · environment_check.py Environment check
Components 11
Lab materials
- Python transition
notebooks/Wk2a_Python_Rapid_Transition.ipynb - Data toolkit
notebooks/Wk2b_Data_Toolkit.ipynb - Student data
data/students.csv - Grade data
data/grades.csv - Messy student data
data/students_messy.csv
Python environment
- Package requirements
requirements.txt - Environment check
src/environment_check.py
Student workflow
- Setup instructions
STUDENT_SETUP.md
Other components
- Student
- GitHub
- Visual Studio Code
Connections 7
- Student → GitHub: creates template
README.md - Student → Visual Studio Code: clones repository
README.md - Student → Package requirements: installs packages
README.md - Student → Environment check: runs check
README.md - Student → Python transition: opens notebook
README.md - Student → Data toolkit: opens notebook
README.md - Student → Setup instructions: follows instructions
README.md