Economics

Economics and Data Science

Module code: L1100
Level 6
15 credits in spring semester
Teaching method: Seminar, Lecture
Assessment modes: Computer based exam, Coursework

In this module you will learn core data science and machine learning techniques and apply them to understand how these tools are transforming empirical work in economics. Data science combines statistical analysis, computational methods, and machine learning to extract insights and make predictions from complex datasets. While economists have traditionally relied on household and firm surveys or administrative records, new and richer forms of data鈥攕uch as satellite imagery, social media activity, and text鈥攁re increasingly shaping economic research. Econometrics has traditionally focused on causal inference, data science emphasises prediction and pattern recognition, offering powerful tools for business and policy.

Module learning outcomes

  • Demonstrate a systematic understanding of data science techniques for analysing complex data.
  • Demonstrate the ability to carry out self-directed study and research, understand the limitations and be able to comment upon research outputs.
  • Demonstrate high level of competence in using computer software to analyse complex data using data science techniques.
  • Demonstrate an ability to communicate advanced concepts and information to specialist and non-specialist audiences.