We Build ML Skills That Actually Work
Since 2019, we've been teaching machine learning to people who want practical knowledge, not just certificates. Our programs focus on real projects and actual understanding.
Our Story
Started with a Simple Question
Back in early 2019, we noticed something odd. Lots of people wanted to learn machine learning, but most courses either dumbed things down too much or went way too academic. There wasn't much in between.
So we tried something different. We started with ten students in a small room in Gò Vấp, teaching them actual ML concepts through real datasets. No fancy promises. Just genuine education focused on understanding how algorithms work and when to use them.
Today we work with professionals across Vietnam who want to add ML capabilities to their skill set. Some are developers, some are analysts, and some are just curious about where technology is heading.
What We Actually Believe In
These aren't values we pulled from a business book. They're things we've learned matter when teaching technical subjects.
Honest Difficulty
Machine learning isn't easy. We tell students that upfront. But we also show them it's learnable if you're willing to work through the tough parts.
Real Practice
You learn ML by building models, breaking them, and fixing them. Our courses include actual datasets and projects that sometimes don't work the first time.
Community Learning
The best insights often come from other students. We create spaces where people can share what worked and what didn't in their projects.
How We Actually Teach This Stuff
Foundation First
We start with the math and statistics you need. Not everything you'd learn in university, but enough to understand what's happening under the hood. Takes about three weeks of focused work.
Small Projects
Before tackling big challenges, you work on smaller ones. Classification problems, regression tasks, basic neural networks. Each project builds on what you learned before.
Real Datasets
Around week six, we introduce messier data. Missing values, outliers, imbalanced classes. The kind of problems you'll actually face when applying ML in real situations.
Final Project
The last month is yours. Pick a problem that interests you, build a solution, and present it. We're there to help, but the decisions are yours to make.
People Who Run This Place
We're a small team. Most of us came from software development or data analysis backgrounds before moving into ML education.
Håkan Lindström
Lead Instructor
Spent eight years building recommendation systems before switching to teaching. Still writes code most weekends because old habits don't really die.
Next Cohort Starts September 2025
We're taking applications for our autumn program right now. Classes run evenings and weekends, designed for working professionals who want to learn ML without quitting their jobs.
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