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Big Data and Machine Learning

Module code: ECOM189

Credits: 15.0
Semester: SEM1

Contact: Dr Daniele Bianchi

Building on the methods and approaches of contemporary applied econometric data analysis developed in Quantitative Methods in Policy Applications, the Big Data and Machine Learning module will equip students with the empirical techniques to use and analyse large datasets. By the end of the course, students will be able to use modern empirical techniques such as machine learning on large microeconomic and financial datasets, assess the informativeness of empirical estimates and their use economic analysis, and visualize complex information sets. Students will learn how to handle real-world data and use econometric software.

Connected course(s): UDF DATA
Assessment: 60.0% Coursework, 40.0% Examination
Level: 7

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