EC915-7-SP-CO:
Data Science for Economics
2024/25
Economics
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 13 January 2025
Friday 21 March 2025
20
20 February 2024
Requisites for this module
(none)
(none)
(none)
(none)
(none)
MSC L14112 Economics with Data Science
This postgraduate module equips students with the key tools in modern data science, with a focus on machine learning (ML) and its application to Economics and Finance.
The aim of this module is:
- To enable students to understand how machine learning tools can complement the tools of traditional econometrics and how to apply these techniques to real-world economics and finance problems.
By the end of this module, students will be expected to be able to:
- Develop a comprehensive understanding of key concepts in modern machine learning (ML): classification, prediction, supervised and unsupervised learning.
- Demonstrate a critical understanding of the advantages and disadvantages of ML as compared to traditional econometric approaches.
- Apply ML to real-world economics and finance problems, with examples based on: Prediction, Causal Inference and Policy Evaluation.
No additional information available.
This module will be delivered via:
- One 2-hour lecture per week.
- One 2-hour lab session every two weeks.
In the lab sessions, students will attempt to solve both theoretical and practical machine-learning problems (the practical problems will be based on R).
These are intended to be face-to-face but can easily be extended to dual delivery or purely online. The lectures will be designed to be inclusive to all, including those with additional learning needs.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Assignment |
|
|
| Exam |
Main exam: In-Person, Open Book, 120 minutes during Summer (Main Period)
|
| Exam |
Reassessment Main exam: In-Person, Open Book, 120 minutes during September (Reassessment Period)
|
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr David Zentler-Munro, email: david.zentler-munro@essex.ac.uk.
Lectures and Classes: Dr David Zentler-Munro
For further information, send an email message to pgteco@essex.ac.uk.
Yes
Yes
Yes
Dr Domenico Moro
university of Birmingham
Lecturer
Available via Moodle
No lecture recording information available for this module.
Economics
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