Financial Analytics with Python

As businesses increasingly try to position themselves to reap benefits from data analytics, accountants are also poised to play a leading role in managing that transition.

In order for them to extend their capabilities, finance and accounting professionals must develop relevant skillsets in order to ensure that they continue to play a key role in driving data analytics initiatives within their organisations.

The objective of this course is to introduce accounting professionals to the recent trends in digital transformation and financial analytics. Participants will be exposed to the skillsets needed by accountants to remain competitive in the digital era, e.g., programming skills.

In particular, this course will focus on the basics of Python programming and the applications of the various packages for data analysis and visualisation, which are important for the day-to-day job of an accountant.

In addition, participants will be able to learn how to extract basic financial data from public sources (such as Yahoo Finance and Quandl) and how these data can be used to plot graphs, charts, and regression analysis to make more informed decisions for their firms. Packages such as numpy, Pandas, matplotlib, and statsmodels will be used as application tools.

Learning Objectives:

• Understand the concept of digital transformation and learn how to use business model canvas to recommend digital transformation practices for firms
• Review the basic statistical concepts and apply them to a financial setting
• Learn basic Python programming
• Perform relevant financial analytics and generate inferences based on the analysis