Machine Learning in Finance: Foundation Course
Starting September 2025, learn how algorithmic trading, risk assessment, and predictive analytics work in real financial markets. This course brings practical skills for anyone interested in where finance meets technology.
What You'll Actually Learn
We've built this program around what people actually need when they want to understand machine learning in financial contexts. No fluff—just the concepts and tools that matter.
Predictive Models
Build systems that forecast market movements. You'll work with real datasets and learn why some predictions work better than others.
Risk Analysis Tools
Understand how banks and investment firms evaluate portfolio risk using machine learning algorithms and statistical methods.
Trading Strategies
Learn the logic behind algorithmic trading systems. We cover how automated systems make decisions and manage positions.
Fraud Detection
See how financial institutions use pattern recognition to identify unusual transactions and prevent fraud in real time.
Course Structure and Timeline
Foundations and Python Basics
Start with financial data handling in Python. We'll cover pandas, numpy, and basic statistical methods that underpin everything else. By week four, you'll be comfortable cleaning and analyzing market data.
Machine Learning Fundamentals
Dive into regression models, classification techniques, and decision trees. Each concept gets applied to financial scenarios—price prediction, credit scoring, and market segmentation.
Advanced Algorithms and Neural Networks
This is where things get interesting. We introduce deep learning for time series forecasting and sentiment analysis using news data. You'll build your own neural network for stock price prediction.
Real-World Applications and Projects
Put everything together in a capstone project. Choose from portfolio optimization, risk management systems, or algorithmic trading strategies. You'll present your findings to instructors and peers.
Meet Your Instructors
Our instructors bring years of experience from both finance and technology sectors. They've worked on real trading floors and built actual risk management systems.
Henrik Westergaard
Lead ML InstructorHenrik spent eight years building quantitative trading systems for a European investment bank before moving into education. He teaches the advanced algorithms module and specializes in neural network applications for market prediction.
Callum Fitzpatrick
Financial Data SpecialistCallum manages risk analytics for a fintech company while teaching part-time. His background in credit risk modeling brings practical perspective to the coursework. Students appreciate his straightforward explanations of complex topics.
Classes Begin September 2025
We're accepting applications through July 2025. The program runs for sixteen weeks with both online and in-person options available. Early enrollment opens in May for those who want to secure their spot.
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