Course Outline
Introduction to Machine Learning in Finance
- The role of AI and ML in the financial industry
- Categories of machine learning (supervised, unsupervised, reinforcement learning)
- Real-world case studies involving fraud detection, credit scoring, and risk modeling
Python and Data Management Fundamentals
- Leveraging Python for data manipulation and analysis
- Analyzing financial datasets with Pandas and NumPy
- Visualizing data using Matplotlib and Seaborn
Supervised Learning for Financial Forecasting
- Linear and logistic regression techniques
- Decision trees and random forest algorithms
- Assessing model performance through accuracy, precision, recall, and AUC metrics
Unsupervised Learning and Anomaly Identification
- Clustering methods such as K-means and DBSCAN
- Application of Principal Component Analysis (PCA)
- Identifying outliers to prevent fraud
Credit Scoring and Risk Assessment Models
- Constructing credit scoring models via logistic regression and tree-based methods
- Managing imbalanced datasets in risk contexts
- Ensuring model interpretability and fairness in financial decisions
Detecting Fraud with Machine Learning
- Overview of common financial fraud patterns
- Employing classification algorithms for anomaly detection
- Strategies for real-time scoring and model deployment
Model Deployment and Ethical AI in Finance
- Deploying models using Python, Flask, or cloud-based platforms
- Addressing ethical considerations and regulatory compliance (e.g., GDPR, explainability)
- Monitoring and retraining models in production settings
Conclusions and Future Directions
Requirements
- Foundational knowledge of statistics and financial principles.
- Familiarity with Excel or comparable data analysis tools.
- Basic programming proficiency, 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
