Machine Learning in Finance Course
Master machine learning applications in finance, focusing on hands-on projects in credit risk assessment, trading model development, and fraud detection systems. Participants will learn to construct, validate, and manage models that enhance profitability, mitigate risks, and adhere to regulatory requirements and ethical guidelines within practical financial operations. This course equips learners with essential tools for real-world deployment.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Acquire expertise in applying machine learning to key financial domains including credit risk modelling, algorithmic trading strategies, and fraud prevention. The course covers essential stages from data preparation and feature development to model validation, backtesting procedures, production deployment, ongoing performance monitoring, and compliance frameworks. Emphasis is placed on ensuring model transparency, fairness, and regulatory adherence to develop dependable, scalable decision-making systems throughout the entire lifecycle.
Elevify advantages
Develop skills
- Build ML credit risk models from raw loan data to calibrated PD scores.
- Design fraud detection pipelines with streaming features, drift control, and KPIs.
- Create and backtest ML trading signals using robust, leak-free time series data.
- Operationalise ML in finance through deployment, monitoring, governance, and audits.
- Apply fair, explainable ML with bias checks, SHAP insights, and regulatory alignment.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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