Course Outline
Introduction to Machine Learning in Finance
- An overview of AI and ML applications within the financial industry
- Classification of machine learning types (supervised, unsupervised, and reinforcement learning)
- Case studies focusing on fraud detection, credit scoring, and risk modeling
Python and Data Handling Fundamentals
- Utilizing Python for data manipulation and analytical tasks
- Analyzing financial datasets with Pandas and NumPy
- Visualizing data using Matplotlib and Seaborn
Supervised Learning for Financial Forecasting
- Application of linear and logistic regression
- Implementation of decision trees and random forests
- Assessing model performance through accuracy, precision, recall, and AUC
Unsupervised Learning and Anomaly Detection
- Exploration of clustering techniques such as K-means and DBSCAN
- Application of Principal Component Analysis (PCA)
- Detecting outliers to prevent fraud
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 processes
Fraud Detection Using Machine Learning
- Identification of common types of financial fraud
- Applying classification algorithms for anomaly detection
- Strategies for real-time scoring and deployment
Model Deployment and Ethics in Financial AI
- Deploying models via Python, Flask, or cloud-based platforms
- Addressing ethical considerations and regulatory compliance (e.g., GDPR, explainability)
- Monitoring and retraining models within production environments
Summary and Recommended Next Steps
Requirements
- Familiarity with fundamental statistics and financial principles
- Proficiency with Excel or comparable 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
