We're Building Something Different Here
Back in late 2023, a couple of us sat down in a coffee shop in Rạch Giá and realized something. The finance world was changing fast with machine learning, but most educational resources either oversimplified everything or drowned students in academic theory. We wanted to create a middle ground that actually worked for people in Vietnam who were curious about this intersection.
How This Started
Our approach came from frustration, honestly. Both of us had spent years trying to explain machine learning concepts to finance professionals, and it never quite clicked the way we wanted. Traditional courses felt disconnected from real-world applications.
So in early 2024, we started small. Just a few weekend workshops, testing what actually resonated with people. Turns out, when you connect algorithmic concepts to actual financial scenarios – like predicting market trends or analyzing risk patterns – things start making sense much faster.
By mid-2024, we had refined our curriculum based on direct feedback from those early participants. And honestly? Their input shaped what we became more than any business plan ever could.
What Drives Our Work
We believe finance education shouldn't feel like decoding ancient texts. Machine learning is already transforming how financial decisions get made – from portfolio management to fraud detection. But there's this gap between the people who understand the tech and those who understand finance.
Our programs focus on bridging that gap. Not by dumbing things down, but by presenting concepts in a context that finance-minded people naturally understand. When someone sees how a neural network can spot patterns in trading data, that's when the real learning happens.
Practical Application
Every concept connects to real financial scenarios you might actually encounter in your career.
Honest Complexity
We don't pretend this stuff is simple, but we break it down into manageable pieces.
Local Context
Examples and case studies reflect the Vietnamese market and regional financial landscape.
Continuous Evolution
Our curriculum adapts as the field changes – because it definitely will.
The People Behind the Curriculum
We're a small team, which means you'll actually get to know us during your learning journey. No faceless corporation here – just people who genuinely care about this intersection of finance and technology.
Kjetil Haugen
Spent seven years building trading algorithms before realizing he preferred teaching people how to think about data. Kjetil handles most of our technical curriculum and has this knack for explaining complex mathematical concepts using everyday examples.
Niilo Virtanen
Comes from a traditional finance background and discovered machine learning almost by accident during a risk management project. Now he focuses on making sure our courses bridge both worlds effectively, drawing on experience from financial institutions across Southeast Asia.
How We Think About Learning
Our teaching philosophy evolved from watching what actually helps people grasp these concepts. Spoiler: it's not endless lectures or purely theoretical exercises.
Context Before Code
We start with the financial problem you're trying to solve, then introduce the machine learning tools that address it. Not the other way around. This approach helps students understand why certain algorithms matter for specific financial applications.
Build As You Learn
Each module includes hands-on projects using real financial datasets. You're not just memorizing formulas – you're actually building models that could be applied to genuine scenarios in portfolio analysis or risk assessment.
Questions Welcome
The best learning happens through dialogue. Our sessions are designed to encourage questions, even the ones that might seem basic. Often those "simple" questions lead to the most interesting discussions about how machine learning actually works in practice.
Realistic Timeframes
We're upfront about the learning curve. Our programs typically run six to nine months because that's how long it actually takes to build solid skills in this field. Anyone promising faster results probably isn't being honest about the complexity involved.
Want to Learn More About Our Programs?
Our next cohort begins in September 2025. We keep class sizes intentionally small to maintain quality interaction, so spots fill up fairly quickly. If you're interested in exploring how machine learning applies to financial analysis, we'd love to hear from you.
Get in Touch