This repository collects my project work from Dr. Angela Yu's 100 Days of Code: The Complete Python Pro Bootcamp. It now includes a full lesson pass across the repo, so each project folder has one canonical lesson.md written in a consistent instructor style.
94day folders are present in this repository.- Each day folder keeps one canonical lesson file:
lesson.md. - Folder names follow the
Day XX - ...pattern and have been compacted where older names were too long. - Later lessons were expanded to match project complexity instead of collapsing into short summaries.
The projects move through the same progression as the course:
- Python fundamentals, control flow, functions, and OOP
- Turtle, Tkinter, PyQt, and game projects
- APIs, JSON, scraping, Selenium, and automation
- Flask apps with templates, forms, auth, and databases
- Pandas, NumPy, Matplotlib, Seaborn, Plotly, and data analysis
- Capstones that combine several skills in one project
Each project lives in its own day folder, for example:
Day 01 - Band NameDay 37 - HTTP Methods and Auth HeadersDay 67 - Flask Blog CMS with EditingDay 77 - NumPy Arrays and Vectorized ComputationDay 100 - Police Deaths in the USA
Most folders contain some combination of:
main.pyor another entry script- notebooks such as
.ipynb - local datasets or static assets
requirements.txtlesson.md
Open the lesson.md inside any day folder first. It explains the project structure, the main concepts, and how to run that specific day.
Many folders can be run directly from their own directory:
cd "Day XX - Project Name"
python main.pySome days use notebooks instead of a single script. For those, open the .ipynb file in Jupyter, VS Code, or Google Colab.
Some day folders include their own requirements.txt. Install dependencies from inside the project folder when needed:
pip install -r requirements.txt- Not every numbered course day appears as a separate folder. Some projects were combined, and the repo reflects the actual project set rather than a placeholder folder for every calendar day.
- Some projects require external services or credentials such as AWS, third-party APIs, or browser automation tooling. Those setup details are documented in the relevant day folder and lesson.
- The repo includes both script-based projects and notebook-based analysis work, so the correct run path depends on the day.