Key information
- Faculty
- Faculty of Social and Historical Sciences
- Teaching department
- Economics
- Credit value
- 15
- Restrictions
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Available to students on the following programmes only: - 果冻影院 MSc Economics, 果冻影院 MSc Data Science and Public Policy (Economics route). Also available to MSc Data Science and Public Policy (Political Science route) with programme director's approval.
- Timetable
-
Alternative credit options
There are no alternative credit options available for this module.
This module aims to provide a rigorous treatment of data science methods, ranging from classical statistical methods to modern machine learning methods. The module provides a detailed mathematical explanation of a number of methods, including supervised and unsupervised learning techniques such as linear regression, logistic regression, additive models, neural networks, random forests, and ensemble learning.
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Module deliveries for 2024/25 academic year
Intended teaching term:
Term 2 听听听
Postgraduate (FHEQ Level 7)
Teaching and assessment
- Mode of study
- In person
- Methods of assessment
-
100%
Exam
- Mark scheme
-
Numeric Marks
Other information
- Number of students on module in previous year
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5
- Module leader
-
Dr Benjamin Deaner
- Who to contact for more information
- economics.dspp@ucl.ac.uk
Last updated
This module description was last updated on 8th April 2024.
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