Course Outline
Introduction to Machine Learning in Finance
- An overview of AI and ML applications within the financial industry
- Categories of machine learning (supervised, unsupervised, reinforcement learning)
- Case studies focused on fraud detection, credit scoring, and risk modeling
Python and Data Handling Fundamentals
- Leveraging Python for data manipulation and analysis
- Exploring financial datasets using Pandas and NumPy
- Data visualization techniques with Matplotlib and Seaborn
Supervised Learning for Financial Forecasting
- Linear and logistic regression
- Decision trees and random forests
- Assessing model performance via accuracy, precision, recall, and AUC
Unsupervised Learning and Anomaly Detection
- Clustering methods (K-means, DBSCAN)
- Principal Component Analysis (PCA)
- Detecting outliers to enhance fraud prevention
Credit Scoring and Risk Modeling
- Developing credit scoring models through logistic regression and tree-based algorithms
- Managing imbalanced datasets in risk-related applications
- Ensuring model interpretability and fairness in financial decision-making
Machine Learning for Fraud Detection
- Common forms of financial fraud
- Employing classification algorithms for anomaly detection
- Strategies for real-time scoring and deployment
Model Deployment and Ethics in Financial AI
- Deploying models using Python, Flask, or cloud platforms
- Ethical considerations and regulatory compliance (e.g., GDPR, explainability)
- Monitoring and retraining models within production environments
Summary and Next Steps
Requirements
- Familiarity with basic statistics and financial principles
- Practical experience with Excel or comparable data analysis tools
- Foundational programming knowledge, 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
