Machine Learning in Finance Course
This course teaches machine learning applications in finance, covering credit risk modelling, fraud detection systems, and trading strategies. Participants will learn to preprocess data, engineer features, build robust models, backtest strategies, deploy solutions, monitor performance, and ensure compliance with governance, fairness, and explainability standards for scalable financial decision-making systems.
flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
Gain expertise in applying machine learning to finance domains like credit risk assessment, algorithmic trading, and fraud prevention. The course covers essential steps including data preprocessing, feature engineering, model development, backtesting, deployment, ongoing monitoring, and governance frameworks. Emphasize building explainable, fair, and compliant models that deliver reliable results in production environments.
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.
- Operationalize 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 the 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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