Big Data Analytics for Accounting and Finance

Python programming language is used in the course. Previous coding experience is useful, but not a prerequisition. However, the course assignments include programming components.

Recommended preliminary course for data analytics and Python programming:

• LASK2057 Introduction to analytics in accounting

Technology requirements: laptop

By the end of the course students will achieve the following intended learning outcomes:
•Students will demonstrate advanced knowledge and critical understanding of data analytics and quantitative methods in accounting and finance.
•Students will analyze and solve complex accounting and finance problems through the integrated application of financial theory, quantitative techniques, and computational
•Students will develop and apply appropriate quantitative models to generate insights from financial and accounting data.
•Students will demonstrate independent research competence by designing and executing an applied analytics project, critically interpreting results, and incorporating ethical considerations into data-driven decision-making.

• Online study resources defined by the instructor
• Datasets distributed by the instructor
• Lecture notes
  Parts of the following books:
  Wes McKinney (2017), Python for Data Analysis, 2nd ed., O’Reilly Media
  Francois Chollet (2017), Deep Learning with Python, 1st ed., Manning Publications
  Stephen Marsland (2014), Machine Learning - An Algorithmic Perspective, 2nd ed., Chapman and Hall/CRC

This course is primarily for accounting and finance students. The total number of participants is restricted (100).