Business Analytics and Big Data

The objective of this course is to provide students with a comprehensive understanding of business analytics. The course focusses on how analytical models (i.e., descriptive, predictive, and prescriptive models) can be used to transform data into actionable insights for decision-making. Business analytics is an interdisciplinary field of research which lies at the intersection of operations research, information systems andmachine learning with the aim of analyzing ‘big’ data data sets and extract meaningful patterns that help organizations solve problems and improvebusiness performance.

Throughout the course, students will gain insights into the following key topics:

1. Understanding core concepts, definitions, and the overall analytics process, as well as exploring practical applications of analytics in various industries.
2. Learning techniques to clean, normalize, and prepare raw data for analysis, ensuring data quality and reliability for accurate modeling.
3. Gaining proficiency in clustering techniques and dimensionality reduction to summarize data and uncover inherent patterns or groupings within large data sets.
4. Applying predictive modeling techniques using both linear and nonlinear models, as well as advanced artificial intelligence models like neural networks. 
5. Extracting insights from unstructured data sources, such as textual data, and learning how to process and analyze textual information to derive meaningful conclusions.

By the end of the course, students will have theoretical and practical knowledge of different methods in business analytics and know a range of analytical methods to solve real-world business problems and improve decision-making.