ES52065: Introduction to programming and machine learning applications in economics and finance
[Page last updated: 14 August 2024]
Academic Year: | 2024/25 |
Owning Department/School: | Department of Economics |
Credits: | 10 [equivalent to 20 CATS credits] |
Notional Study Hours: | 200 |
Level: | Masters UG & PG (FHEQ level 7) |
Period: |
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Assessment Summary: | PRPR 100% |
Assessment Detail: |
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Supplementary Assessment: |
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Requisites: | |
Learning Outcomes: |
At the end of the unit students, should be able to:
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Synopsis: | Study the principles of programming and methods of machine learning.
You'll gain practical skills in:
- reading and writing programmes
- producing programmes to solve real-world problems, primarily in the machine learning domain
You'll also explore the relevance of taught machine learning methods to economics and finance. |
Content: | Programming tools and software for implementation of machine learning methods, for example, in Python.
Supervised and unsupervised machine learning and its algorithms in application to economic and financial problems.
Applications of machine learning in economics and finance. |
Course availability: |
ES52065 is Optional on the following courses:Department of Economics
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Notes:
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