Machine Learning in Financial Services using Python and Excel

Machine learning is increasingly being employed in financial services to spot underlying patterns in data that are difficult to discern using conventional analysis techniques.  This course covers Machine Learning Fundamentals, provides an overview of using Python in Excel, and leaves delegates with a basic functional toolset for building Machine Learning models in Excel and/or Python.

Who should attend? 

This is perhaps best answered by a few examples of what machine learning is used for in the financial services arena.  Please note that there’s no deep dive into any one topic and that not all of these will be covered on the course. 

 

Common Applications of Machine Learning in Financial Services: 

Credit risk  

Credit scoring  

Debt collection  

Fraud detection  

Insurance underwriting 

Investments  

Portfolio management  

Trading (equities, forex etc 

 

Learning Modules: 

Machine learning introduction 

Build a machine learning model directly in Excel 

Machine learning with Python 

Combining Python and Excel 

General pitfalls 

Prerequisites: 

Excel proficiency: Intermediate or above 

Excel version: 2013 or later (desktop versions only)  

Windows 10 

Sufficient rights to install software on the course* 

Software required* 

Python 

Python modules 

PyXLL – Excel AddIn FREE trial version (NB. Only install 2-3 days prior to the workshop start) 

 

*The software installation forms part of the course; however a manual will be provided to delegates who need their IT department to pre-install software. 

 

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