Welcome! This repository is designed to support your continued growth as a programmer after completing the Code:You program. It provides additional learning resources and hands-on projects to help solidify your understanding and prepare you for real-world coding environments.
We strongly encourage you to explore each topic by building small projects of your own. The goal is to deepen your learning so that working with real codebases feels less overwhelming and more intuitive.
Note: Most projects here go high level so additional research will be needed on your end.
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MarkDown Notes This is a great cheat sheet to set your projects apart from the competition! Having a good looking notebook speaks volumes to your work.
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production_pipeline
This project uses the Pokémon API to demonstrate how a data science project can evolve from a simple notebook into a structured set of Python scripts. It introduces concepts like modular code, file organization, and reproducibility. -
python_oop_classes_example
This notebook introduces Object-Oriented Programming (OOP) in Python. It builds on your knowledge of functions and explores how classes can be used to organize and extend functionality in more powerful ways. -
tests This project covers writing test in python and talks about Test Driven Development. This uses classes so its important to work on them first.
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speed In this section, we explore strategies for writing more efficient, readable, and scalable Python code. By leveraging tools like
%%timeit, we’ll measure and compare execution times directly within Jupyter notebooks to gain insight into how different approaches affect performance. -
GitHub Actions This covers getting started with GitHub Actions. Covers what they are and how they work.
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NYC Taxi Project Small project putting together many of the things we covered in the various other projects. Show taking simple code from a notebook to making it production ready.
The Break-Fix projects are intentionally open-ended and sometimes loosely structured. You’ll be given a clear question or problem to solve, but beyond that, instructions may be minimal or vague. Some projects will introduce technologies we won’t cover directly and where not in the classes, but you’ll always have enough information to get started.
Solutions will be provided for the core problems, but some projects may include optional bonus tasks without answers or hints. This is designed to mimic real-world scenarios where you’re handed a task and expected to figure out how to deliver results. Sometimes you’ll have guidance or someone to ask for help—other times you’ll need to find your own way forward.
This process can feel frustrating or overwhelming at times, that’s completely normal and part of the learning experience. Stick with it, and by the time you’re on the job, you’ll feel much more confident tackling similar challenges.
| Command | Linux/Mac | GitBash |
|---|---|---|
| Create | python3 -m venv venv |
python -m venv venv |
| Activate | source venv/bin/activate |
source venv/Scripts/activate |
| Install | pip install -r requirements.txt |
pip install -r requirements.txt |
| Deactivate | deactivate |
deactivate |
Each sub-project contains its own README with detailed explanations, so feel free to dive into them directly when you're ready. Happy coding!