| Overview | Topics Covered |
|---|
Day 1:
| - Overview of AI/ML and analytics in Finance
- Applications and potential of AI and Analytics
- Governance of AI/ML in Finance
- Basic coding and revision with Python
|
Day 2:
| - Supervised learning methods
- Logistic regression, tree methods, Naïve Bayes
- Case Study of fraud detection and loan approvals
|
Day 3:
| - Unsupervised learning methods
- Clustering methods
- Case Study in compliance: Know Your Customer/Anti-money Laundering
|
Day 4:
| - Unstructured (text) data in finance
- Large Language Models (LLMs) in Finance (e.g. ChatGPT)
- Case Study in investment analysis and compliance
|
Day 5:
| - Agentic AI in Finance
- Overview of advances in AI/ML in finance
- Case Study: Streamlining processes in finance
|
There is a good balance of AI concepts, business applications, demos and hands-on practice to reinforce your learning and application throughout the 5-day course.
Laptop required during session: Please note that participants are required to bring their own laptop for this practical, hands-on course.
For more information on the intake dates, trainers and programme fee, please click here.
