After two Data Science & Machine Learning cohorts, we noticed the same bottleneck showing up again and again: participants who were genuinely excited about machine learning, but who got stuck on Python itself (syntax, data structures, functions) before they ever reached a model. In April 2026 we ran Python for Everyone, a bootcamp built to close that gap on its own, for anyone starting from zero.
The gap we kept seeing
Our Data Science & Machine Learning bootcamps assume a working baseline in Python, enough to read a script, write a loop, and follow along with a Jupyter Notebook. Across the first two cohorts, the participants who struggled most weren't struggling with regression or clustering; they were spending their limited time catching up on plain programming fundamentals mid-cohort, which left less room for the machine learning content the bootcamp was about.
The fix wasn't to water down the DS/ML curriculum. It was to give programming fundamentals a home of their own, ahead of time.
Beginner to builder
Python for Everyone doesn't touch data science or machine learning at all. It's a general-purpose programming bootcamp with one goal: take someone from zero programming knowledge to being able to build real, working Python projects, full stop. Every concept is introduced, then immediately applied, rather than left as theory.
What the curriculum covers
- Python fundamentals, variables, data types, and the basic building blocks of a program
- Operators and conditions, the logic that lets a program make decisions
- Git & GitHub basics, enough version control to submit and track work the way real projects do
- Collections and loops, lists, dictionaries, and iterating over data
- Functions, breaking a program into reusable, testable pieces
- File handling and error handling, reading and writing real files, and failing gracefully when something goes wrong
- Object-oriented programming, classes, objects, and structuring larger programs
- Building real projects, putting every prior lesson together into something that runs
Three real projects
Rather than ending with a single capstone, Python for Everyone builds toward three separate projects spaced across the curriculum: a Study Log project after the Functions lesson, a Personal Catalog project after File Handling and Error Handling, and a final Student Management System that pulls together collections, functions, file handling, and object-oriented programming into one working application.
Why Git & GitHub shows up in lesson three
Lesson Three sits in an unusual spot for a Python bootcamp, it's not about Python at all. It's about Git and GitHub. We put it there deliberately: from that lesson on, every homework and assignment gets submitted the way real code ships: through a repository and a pull request instead of a zipped folder in a group chat.
One lesson turned out to be enough to get people committing and pushing their homework. It wasn't enough to make them confident, independent Git users, branching, resolving a merge conflict, opening a clean pull request on someone else's repository. That specific gap is what led, a couple of months later, to a bootcamp built entirely around Git and GitHub.
Open and free
Like every bootcamp in this series, Python for Everyone was fully sponsored by Dugsiiye, so every seat was free. All fourteen lessons, homework assignments, and projects are public in the apr-python-for-everyone-bootcamp repository on GitHub, released under a Creative Commons BY-NC-SA 4.0 license.
What comes next
With a dedicated Python track now in place, the Data Science & Machine Learning cohort that followed could spend less time re-teaching basic syntax and more time on the ML workflow itself, and the collaboration gap this bootcamp surfaced in Lesson Three became the starting point for our next program, built entirely around Git and GitHub.
Writing about Somali language technology, open data, and AI from the lab in Mogadishu.