Machine Learning Mastery Program

Join our comprehensive 18-month journey into practical machine learning applications. Starting September 2025, learn from industry veterans who've built real systems at scale.

Reserve Your Spot

What You'll Actually Build

Forget theoretical exercises. Our students work on real projects that mirror what you'll encounter in the field. By month six, you're deploying models that solve actual business problems.

  • Build recommendation systems like Netflix uses for content discovery
  • Create fraud detection models that banks actually rely on
  • Develop computer vision applications for manufacturing quality control
  • Design NLP systems that handle customer service automation
  • Deploy models to cloud infrastructure with proper monitoring
  • Work with messy, real-world datasets that don't come pre-cleaned

We've structured everything around hands-on learning because that's how you retain knowledge. Each module builds on the previous one, so by graduation you have a portfolio that demonstrates genuine capability to potential employers.

Students collaborating on machine learning project with laptops and data visualizations

Program Structure & Timeline

Learning Phase
Duration
Focus Area
Deliverable
Foundation Phase
Months 1-4
Python, Statistics, Core ML
Data Analysis Project
Application Phase
Months 5-10
Deep Learning, Computer Vision
Image Classification System
Specialization Phase
Months 11-15
NLP, Recommendation Systems
Production ML Pipeline
Capstone Phase
Months 16-18
Industry Project
Portfolio-Ready Application

Weekly Commitment

Plan for 15-20 hours per week including live sessions, project work, and self-study. Most students find this manageable alongside full-time work with proper time management.

Prerequisites

Basic programming experience in any language (we'll teach Python), high school mathematics, and genuine curiosity about how machines learn patterns from data.

Class Schedule

Two live sessions per week (Tuesday 7PM, Saturday 10AM Taiwan time) plus optional Friday office hours. All sessions recorded for different time zones.

Starting Date

September 15, 2025. Early bird applications close July 1st. We accept maximum 24 students per cohort to maintain quality interaction and personalized feedback.

Your Instructors

Thom Eriksson, Lead ML Engineer

Thom Eriksson

Lead ML Engineer

Spent six years at Tesla working on Autopilot perception systems. Before that, built recommendation engines at Spotify. He's the guy who explains complex algorithms using everyday examples that actually make sense.

Computer Vision Deep Learning Model Deployment
Viktor Petrov, Data Science Director

Viktor Petrov

Data Science Director

Led ML initiatives at three fintech startups, two of which got acquired. His fraud detection work at payment processors helped prevent millions in losses. Viktor teaches the business side of ML that bootcamps usually skip.

Fraud Detection Time Series MLOps
Alexei Rosetti, NLP Specialist

Alexei Rosetti

NLP Specialist

Former research scientist at Google DeepMind, now consulting for healthcare companies on medical text analysis. His chatbot work handles customer queries for several major e-commerce platforms across Asia.

Natural Language Processing Transformers Chatbots
Marco Castellano, Infrastructure Lead

Marco Castellano

Infrastructure Lead

Built the ML infrastructure at Grab that handles millions of ride predictions daily. Marco knows how to make models work reliably in production, not just in Jupyter notebooks. He'll teach you the engineering that matters.
Cloud Architecture Model Scaling Production Systems