Advanced Time Series

Undergraduate | 2026

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area/catalogue icon
Area/Catalogue
MATH X400
Course ID icon
Course ID
207627
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
4
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

Course overview

In this course students will learn advanced approaches to time series analysis. This will necessarily include multivariate time series and deep learning approaches to time series analysis but may also include topics such as state space models and Kalman filters, Bayesian time series, GARCH processes and Score driven models, anomaly detection methods or the integration of temporal and non-temporal data into a single model.

Course learning outcomes

  • Evaluate the structure of complex time series data and recommend appropriate analysis
  • Investigate complex time series data using contemporary analytical methods
  • Critically review the application of time series analysis to ensure appropriate use
  • Interpret time series analysis for both specialist and non-specialist audiences

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A