Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to AI in the Financial Sector
- Overview of AI applications in finance (fraud detection, algorithmic trading, risk assessment)
- Introduction to data analysis principles and types of financial data
- Ethical considerations and regulatory compliance in AI implementation
- Setting up Python/R environment for financial data analysis
Data Collection and Preprocessing
- Data sources in the financial sector (stock data, market indices, customer data)
- Data cleaning, normalization, and transformation techniques
- Feature engineering for enhanced data analysis
- Preprocessing a financial dataset for analysis
Machine Learning Algorithms for Financial Data
- Supervised learning algorithms (linear regression, decision trees, random forest)
- Unsupervised learning for anomaly detection (k-means clustering, DBSCAN)
- Case study analysis: Credit scoring models and risk management
- Building a supervised model for predicting stock prices
Advanced AI Techniques and Model Optimization
- Deep learning models for financial data (LSTM for time-series forecasting)
- Introduction to reinforcement learning for decision-making in trading strategies
- Hyperparameter tuning and model validation
- Implementing LSTM for financial time-series data
Visualization, Interpretation, and Reporting
- Data visualization best practices using libraries (Matplotlib, Seaborn, Tableau)
- Interpreting model outputs for business insights
- Creating comprehensive reports for stakeholders
- Analyze and present financial data using a complete AI workflow
Summary and Next Steps
Requirements
- Basic knowledge of Python/R programming
- Understanding of financial terminology and basic statistics
Audience
- Financial analysts
- Data scientists
- Risk managers
28 Hours
Testimonials (1)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
