Organization Clock — Eastern Time (ET) · Miami, FL () Eastern Time ·
Volume I · Code Crunch Worldwide Est. 2024 Free to learn from

Code Crunch
Convos.

A fifteen-week Python bootcamp — designed for the absolute beginner, sharpened to the standards of professional engineering. Five hundred and forty hours of lectures, labs, projects, and a capstone. No cost.

15weeks
Program length
540hrs
Total workload
14+1
Projects + capstone
$0
Tuition · always

§ I · The Program

An open course, in the open.

Code Crunch Convos began in August 2024 as a small interview-prep workshop run by Code Crunch Worldwide — a global, community-led community. It ran quietly through its first year and a half while we built out the branding, website, assessments, and event programming behind the scenes. In 2026 we rebuilt it as a complete fifteen-week Python bootcamp — a public curriculum that any learner, anywhere, can use without permission or payment.

The course is structured like a real-world bootcamp: lectures, hands-on labs, weekly projects, quizzes, homework, and a portfolio capstone. It is engineered to be taken on its own, or taught from by instructors and university clubs. Everything is free to learn from and lives on GitHub.

“The best way to predict the future is to teach it.” — Code Crunch Worldwide

§ II · Who It's For

Built for four kinds of learner.

No prerequisites beyond a willingness to read documentation and roughly thirty-six hours a week. There is room for everyone.

No. 01

The Absolute Beginner

Has never written code. Week 1 begins with installing Python and ends with their first commit on GitHub.

No. 02

The Self-Taught Coder

Has dabbled in tutorials. Wants structure, accountability, and a portfolio of finished, polished work.

No. 03

The Career-Switcher

Needs hire-ready Python skills, version control habits, and projects to show — all without paying for a paid bootcamp.

No. 04

The Instructor

Teaches a community group or a class. Wants a ready-to-deliver, modifiable curriculum that they can fork and adapt.

§ III · The Five Phases

From terminal to capstone, in five movements.

The arc of the program is composed in five phases — each builds on the last, like chapters of a book.

Phase i · Wk. 01—04

Foundations

Set up the development environment. Master the absolute basics: variables, types, operators, control flow, and the function as a unit of thought.

Phase ii · Wk. 05—07

Core Programming

Choose the right data structure. Read and write files reliably. Begin to think in objects and design clean class hierarchies.

Phase iii · Wk. 08—11

Real-World Python

Call APIs over HTTP. Build a small web app with Flask. Speak SQL fluently. Adopt the engineering habits — tests, CI, code review.

Phase iv · Wk. 12—14

Applied Python

Automate the tedious. Analyze real data with pandas and NumPy. Train and evaluate a machine-learning model — and learn when not to.

Phase v · Wk. 15

Capstone

Ship a substantial, public, portfolio-grade project across one of five tracks. README, tests, CI, deploy, video walkthrough.

§ IV · The Curriculum

Fifteen weeks, week by week.

Each entry below corresponds to a folder in the GitHub repository, containing lecture notes, exercises, challenges, a quiz, homework, and a mini-project.

01

Python Foundations & Dev Environment

Installing Python · REPL vs scripts · terminal basics · virtual environments · pip · Git and GitHub · your first commit.

Mini-project

“Hello, You” — a personal CLI greeter

02

Variables, Data Types & Operators

int, float, str, bool, None · type casting · arithmetic, comparison & logical operators · string methods · f-strings · type hints.

Mini-project

Unit converter CLI

03

Control Flow — Conditionals & Loops

if / elif / else · truthiness · while and for loops · range, enumerate, zip · break, continue · the loop-else clause · nested loops.

Mini-project

Number-guessing game with replay

04

Functions, Modules & Scope

def syntax · parameters, return values, defaults · *args / **kwargs · LEGB scope rule · lambdas · importing · writing your own module.

Mini-project

Personal finance calculator

05

Data Structures & Comprehensions

Lists, tuples, sets, dicts · mutability · nested data · list / dict / set comprehensions · generator expressions · Big-O intuition.

Mini-project

Contact book manager

06

File I/O & Exception Handling

open() and the with-statement · pathlib · the csv and json modules · the exception model · try / except / finally · custom exceptions · logging.

Mini-project

Log file analyzer

07

Object-Oriented Programming

Classes, instances, self · inheritance & composition · super() · dunder methods (__repr__, __eq__, …) · properties · @dataclass.

Mini-project

Library management system

08

APIs, JSON & HTTP

HTTP methods and status codes · the requests library · query params, headers, auth · pagination and rate limits · producing and consuming JSON.

Mini-project

Weather dashboard CLI

09

Web Development with Flask

Routes, request & response · Jinja2 templates · static files · HTML forms · sessions and flash messages · deploying for free.

Mini-project

Personal blog web app

10

Databases & SQL with Python

The relational model · SQL CRUD · JOINs and GROUP BY · SQLite from Python · parameterized queries · intro to the SQLAlchemy ORM.

Mini-project

Task tracker with SQLite

11

Testing, Debugging & Code Quality

pytest, fixtures, parametrize · mocking · coverage · the pdb debugger · ruff and black · mypy · pre-commit · GitHub Actions CI.

Mini-project

Tested utility library + CI pipeline

12

Automation & Scripting

argparse for CLI tools · subprocess, pathlib, shutil · scheduling with cron · web scraping with BeautifulSoup · ethics of automation.

Mini-project

File organizer bot

13

Data Analysis with pandas

NumPy arrays and broadcasting · pandas Series and DataFrame · loading, cleaning, joining · groupby and pivot tables · plotting with matplotlib.

Mini-project

Real-world dataset analysis

14

Intro to AI/ML with scikit-learn

Supervised vs unsupervised · train/test split · linear & logistic regression, decision trees, k-NN · pipelines · evaluation metrics · bias & fairness.

Mini-project

Spam classifier

15

Capstone Project

A polished, public project of your choice. README, tests, CI, deployment, a video walkthrough. Pick one of five tracks: Web · Data · ML · Automation · API.

Deliverable

Your portfolio centerpiece

§ V · The Weekly Rhythm

Thirty-six hours, balanced.

Each week is designed to add up to roughly thirty-six hours of learning — spread across study, practice, projects, and reflection. Part-time learners can stretch the program to thirty weeks at half-pace without changing the content.

ComponentHours / week
Lectures & readings6
Hands-on exercises8
Coding challenges4
Quizzes & references3
Homework problems6
Mini-project7
Self-study & review2
Total36

The work is project-based by design. Every week culminates in a small shipped artifact — a script, a CLI tool, a web page, a tested library — that is pushed to a public GitHub repository. By the end of week fourteen, you have fourteen small projects in your portfolio. Week fifteen turns that into a capstone you would be proud to put on a résumé.

Reading the documentation is treated as a skill in itself. We cite the official Python docs constantly, never as a chore but as a habit you will rely on for the rest of your career.

§ VI · Tooling

Free, open, and cross-platform.

No paid platforms. No proprietary dependencies. No required SaaS. Every tool below works on macOS, Windows, and Linux.

Language
Python 3.11+
python.org
Editor
VS Code
free · cross-platform
Version Control
Git + GitHub
free for public repos
Environments
venv · uv
isolated installs
Format / Lint
ruff · black
opinionated, fast
Testing
pytest
w/ coverage
Web
Flask · Jinja2
minimal framework
Database
SQLite · SQLAlchemy
no server required
HTTP
requests · httpx
de facto clients
Data
NumPy · pandas
the analytics stack
Plotting
matplotlib
via pandas .plot
Machine Learning
scikit-learn
classical ML

§ VII · Skills You Will Carry

What you walk away with.

By the end of Week 15, you are able to do each of the following — credibly, on a real codebase, in front of real reviewers.

§ VIII · The Capstone

One project. Five tracks. Your choice.

Week 15 is reserved for a substantial, public project of your choosing. Pick the track that excites you most. Each track has a worked example in the repository.

Track i

Web App

A Flask application with database, multiple routes, and one significant interactive feature.

Track ii

Data

A real public dataset analyzed end-to-end, with cleaning, EDA, and a written summary of findings.

Track iii

Machine Learning

Train a scikit-learn model, evaluate it honestly, and ship a CLI or web endpoint for inference.

Track iv

Automation

A working tool that solves a real problem — in your school, your community, your daily life.

Track v

API

A small REST API with documentation, tests, authentication, and a deployed demo.

§ IX · Getting Started

Four commands. Then begin.

The setup is intentionally lightweight. If you can run a terminal command, you can begin the bootcamp today.

# 1. Clone the curriculum repository
git clone https://github.com/CODECRUNCHWORLDWIDE/C1-Code-Crunch-Convos.git
cd C1-Code-Crunch-Convos

# 2. Create a virtual environment
python -m venv .venv
source .venv/bin/activate    # macOS / Linux
.venv\Scripts\activate       # Windows

# 3. Open the Week 1 README and begin reading
code curriculum/week-01-python-foundations/README.md

# 4. Push your first mini-project to your own GitHub by Sunday
git push origin main

Need help installing Python or Git first? Visit the setup guides for macOS, Windows, Linux, and browser-only.

§ X · Why Free

Education without paywalls.

Code Crunch Convos is free to learn from. Read it, download it, run the code, build your projects from it, publish those projects as your own work. No tuition, no paywall on the material, no account required.

We made this choice deliberately. A curriculum that only opens up after payment is, in our view, no curriculum at all. What free does not mean is unowned: the curriculum stays ours, so that it stays coherent, stays maintained, and stays worth the standards it claims to meet.

The tools we teach are open source. If you want to teach this course, translate it, or build something on top of it, that is welcome — it just starts with a message rather than a fork, and the answer is usually yes.

Read the contributing guide

§ XI · Frequently Asked

Questions, anticipated.

Is this really free?

Yes. The whole curriculum is free to learn from — no paid tier, no upsells, no required services. The only thing it costs you is time and effort.

Do I receive a certificate?

Not by default — we are a community-built open curriculum, not an accredited institution. Your public GitHub portfolio of fifteen shipped projects is the credential that matters most to employers. Communities or universities running this as a cohort may issue their own certificates.

How long does the bootcamp realistically take?

Designed for ~36 hours/week × 15 weeks (~540 hours). Most self-paced learners take 6–12 months at part-time speed. Finishing matters more than speed.

Where are the answers?

On the page that asked the question. Every exercise, challenge, homework problem and mini-project carries its own complete, explained solution under The Solution, with a runnable file beside it whose code matches the block you read. Nothing is hidden behind a toggle, and there is no separate answers folder anywhere in the course. Attempt it first, then read the answer and compare — a learner working alone at midnight has no one else to check against.

I already know a little Python. Can I start later?

Yes. Each week opens with a quiz — if you score above eighty percent, the topic is safe to skim. We recommend at least glancing at earlier weeks for any unfamiliar habits (especially Git and testing).

Can I teach this in my community or classroom?

Please do. Fork the repository, adapt as needed, and — if your adaptation works well — open a pull request so others can learn from your improvements. See the contributing guide.

What happens after Week 15?

You specialize. Pick a deeper track: web (Django/FastAPI), data (more SQL + visualization), ML (deep learning), DevOps, or systems. Contribute to open source. Build more projects. Apply for roles. Mentor someone going through this curriculum.

Can I use AI assistants while working through the course?

Yes — for explanations, debugging help, and reviewing code you have written yourself. No — for generating solutions you do not understand. The shortcut is the price you pay later, in interviews you cannot pass and codebases you cannot maintain.

§ XII · Begin

Fifteen weeks from now,
you will have shipped fifteen projects.

Open the repository. Read Week 1. Push your first commit by Sunday.