The primary objective of this course is to introduce participants to the main models and techniques for extracting, mining, and analyzing big data. Specifically designed to complement traditional accounting and finance techniques, this course focuses on handling data without a predetermined structure (e.g., text), non-linear data, and data sets whose size poses challenges for analysis using traditional methods. 

This course is designed for professionals in accounting, finance, data analytics, and related fields who seek to enhance their skills in handling and analyzing large and unstructured data sets.

Throughout the course, participants will be introduced to a variety of techniques and models tailored for big data analysis. These include but are not limited to:

Data Visualization: Tools and techniques for visualizing large and complex data sets to aid in interpretation and decision-making.

Machine Learning Algorithms: Application of machine learning algorithms for predictive analysis and pattern recognition in non-linear data sets.

Text Mining: Techniques for extracting valuable insights from unstructured text data.

Natural Language Processing (NLP): Methods for processing and analyzing human language data, enabling sentiment analysis, topic modeling, and more.

eclass: https://eclass.uop.gr/courses/1832/