Course Outline
Introduction to Machine Learning in Finance
- An overview of AI and ML applications within the financial sector.
- Classifications of machine learning (supervised, unsupervised, and reinforcement learning).
- Real-world case studies covering fraud detection, credit scoring, and risk modeling.
Fundamentals of Python and Data Handling
- Leveraging Python for data manipulation and analysis.
- Analyzing financial datasets using Pandas and NumPy.
- Creating data visualizations with Matplotlib and Seaborn.
Supervised Learning for Financial Forecasting
- Techniques including linear and logistic regression.
- Algorithms such as decision trees and random forests.
- Assessing model performance through accuracy, precision, recall, and AUC.
Unsupervised Learning and Anomaly Detection
- Clustering methods, including K-means and DBSCAN.
- Principal Component Analysis (PCA) for dimensionality reduction.
- Identifying outliers to enhance fraud prevention.
Credit Scoring and Risk Modeling
- Developing credit scoring models using logistic regression and tree-based algorithms.
- Managing imbalanced datasets in risk-related applications.
- Ensuring model interpretability and fairness in financial decision-making.
Fraud Detection via Machine Learning
- Identifying common types of financial fraud.
- Applying classification algorithms for anomaly detection.
- Strategies for real-time scoring and model deployment.
Model Deployment and Ethics in Financial AI
- Deploying models using Python, Flask, or cloud-based platforms.
- Addressing ethical considerations and regulatory compliance (e.g., GDPR, explainability).
- Monitoring and retraining models within production environments.
Recap and Future Directions
Requirements
- A solid understanding of basic statistics and financial principles.
- Experience using Excel or similar data analysis tools.
- Foundational programming skills, ideally in Python.
Target Audience
- Financial analysts.
- Actuaries.
- Risk officers.
Testimonials (5)
Possible applications /exercises
Estelle De la Fouchardiere - Advanced Bionics AG
Course - Machine Learning & AI for Finance Professionals
I really enjoyed seeing how using this tool can really improve and automate work. I also appreciated the initial part where we were helped to eliminate our prejudice against artificial intelligence. The examples are wonderful.
chiara di egidio - Advanced Bionics AG
Course - Machine Learning & AI for Finance Professionals
I liked to get knowledge about new possibilities
Maciej Karolczak - Advanced Bionics AG
Course - Machine Learning & AI for Finance Professionals
I like the examples, so we have an idea of what is possible
Deborah Highes
Course - Machine Learning & AI for Finance Professionals
it has opened my mind to new tool that can help me in creating automation
