Machine Learning for Financial Streams
Financial markets move faster than human reaction time. We built this program because traditional analysis tools can't keep up with the speed of modern data streams coming from exchanges across Asia.
Our approach differs from typical courses. Instead of teaching theory first, we start with real market data from Thai and regional exchanges. You'll work with actual streaming feeds from day one.
This six-month program begins in September 2025. We accept twelve participants per cohort to maintain quality and allow proper mentorship. Applications open in June.
What You'll Actually Learn
Stream Processing
Market data arrives continuously. We'll teach you to process thousands of data points per second without losing information. You'll build pipelines that handle real exchange feeds.
Pattern Recognition
Markets repeat behaviors, but not exactly. You'll train models to spot these patterns in noisy data. We focus on techniques that work with limited historical data.
Risk Modeling
Every prediction carries uncertainty. You'll learn to quantify that uncertainty and build systems that account for what they don't know. This module draws from our Bangkok team's experience.
Data Infrastructure
ML models need clean data. We'll show you how to build reliable data pipelines that handle market holidays, exchange outages, and time zone differences across ASEAN markets.
Production Systems
A model that works on your laptop might fail in production. You'll learn deployment practices that keep systems running during high volatility periods when they matter most.
Backtesting Reality
Most backtests lie. We'll teach you why and how to build honest testing frameworks that account for transaction costs, slippage, and the dozen other things that kill strategies in live trading.
Six Months From Start to Finish
Months 1-2: Foundations
We start with streaming data fundamentals. You'll connect to live market feeds and build your first processing pipeline. No prior ML experience needed, but you should be comfortable writing Python code. We cover the math as we go, when you actually need it.
Months 3-4: Model Building
Now you'll train your first models on real data. We use actual market situations from 2023-2024, including some interesting volatility events. You'll learn what works and what doesn't through direct experience rather than lectures.
Months 5-6: Capstone Project
Your final project involves building a complete system from data ingestion to model deployment. You'll work with a mentor from our team who reviews your work weekly. Past projects have focused on currency pairs, regional equities, and commodity futures.
Stories from Past Participants
Vikram Joshi
Data Analyst, BangkokI came from traditional business intelligence work. The jump to real-time ML felt steep at first, but the instructors matched the pace to our cohort. What helped most was working with actual market data from regional exchanges rather than cleaned datasets from textbooks.
Freya Lindqvist
Software Developer, PhuketThe program didn't promise anything unrealistic. They were upfront about the learning curve and the work required. My capstone project focused on Thai equity data, and I still use parts of that system in my current role. The mentorship during those final two months made the difference.
Applications Open June 2025
Our September cohort will be our third run of this program. We've refined the curriculum based on feedback from previous participants. The time commitment is significant - expect 15-20 hours per week including live sessions and project work.
If you're interested in learning more about the application process or have questions about the program structure, reach out to our team.