Our Biggest Cohort Yet: Inside the June 2026 Data Science & Machine Learning Bootcamp
ProgramsJul 29, 2026 · 7 min read · La cusboonaysiiyay Aug 10, 2026
Our Biggest Cohort Yet: Inside the June 2026 Data Science & Machine Learning Bootcamp
In June 2026 we ran our third Data Science & Machine Learning Bootcamp, and it's the biggest curriculum we've built for the program — eight core lessons on the full ML workflow, plus seven bonus sessions covering deep learning, generative AI, ethics, and career paths.
In June 2026 we ran our third Data Science & Machine Learning Bootcamp, and it ended up being the biggest curriculum we'd built for the program — eight core lessons covering the full ML workflow, plus seven additional bonus sessions covering everything from the math underneath machine learning to career advice for people about to go looking for their first data role.
Three Cohorts In
By June 2026 we'd already run the September 2025 and February 2026 Data Science & Machine Learning cohorts, plus Python for Everyone in between. That last one mattered more than we expected: participants arriving at this cohort were far more likely to already have working Python fluency, which meant the full month could go toward data science and machine learning itself, instead of also being a crash course in the language underneath it.
The Same Core Seven Stages
The underlying philosophy hasn't moved since the first cohort: collect data, preprocess it, split it into train and test sets, choose a model, train it, evaluate it, deploy it. Every cohort we run is a different arrangement of lessons around that same seven-stage backbone.
Eight Lessons, Not Ten
This cohort restructured the core material into eight lessons, opening with something the earlier cohorts didn't have: a standalone lesson on what data science actually is, as its own discipline, before moving into machine learning specifically.
Lesson One — Data Science, framing the field before diving into ML
Sii daynta xogta, kooxo bootcamp cusub, waraaqo cilmi-baaris, iyo cusboonaysiinta shaybaarka — toos ugu socda sanduuqaaga. Spam ma jiro, waad ka bixi kartaa markasta.
Lesson Five — Regression, in both theory and a live "in action" walkthrough
Lesson Six — Classification, split across a theory session and two hands-on practice sessions
Lesson Seven — Clustering, again paired theory with practice
Lesson Eight — Deployment
Seven Bonus Sessions
This was also the first cohort to go beyond the core workflow entirely. After two prior runs, a consistent set of questions kept coming up that the core lessons were never designed to answer — how does this connect to deep learning, what's actually going on with generative AI, and what does a career in this field even look like. We built seven bonus sessions specifically to answer them:
Math for Data Science & Machine Learning
Introduction to Deep Learning
AI & Generative AI
AI Ethics & Responsible AI
Career Path in Machine Learning
Building a Strong Portfolio
Final Instructor Advice
The Final Project
The bootcamp still closes the way every cohort has: a deployment lesson, followed by a final project that asks each participant to run the full workflow themselves, from a fresh dataset to a deployed result, without a lesson video to follow along with.
Open and Free
As with every cohort in this series, the bootcamp was fully sponsored by Dugsiiye, keeping every seat free. The full curriculum — core lessons, bonus sessions, assignments, and the final project — is public in the Jun-ds-ml-bootcamp-2026 repository on GitHub under a Creative Commons BY-NC-SA 4.0 license.
What Comes Next
Three Data Science & Machine Learning cohorts and a Python bootcamp in, one gap was still showing up in almost every project submission: participants who could build a model but weren't confident collaborating on code the way a real engineering team does. That gap became our next bootcamp, built entirely around Git and GitHub.
Python for Everyone: Teaching the Language Our Data Science Bootcamps Assumed You Already Knew
After two Data Science & Machine Learning cohorts, we kept seeing the same bottleneck: people excited about ML who got stuck on plain Python before they ever reached a model. Python for Everyone is the bootcamp we built to close that gap on its own.
