COMPX523

Machine Learning for Data Streams

2027

15

500

A Trimester

Hamilton

COMPX305 or COMPX310 or COMP316 or COMP321 and a further 30 points at 300 level in Computer Science and/or any Engineering subject.

COMP423, COMP523

Data streams are everywhere, from F1 racing telemetry and electricity networks to social media feeds and financial markets. This course focuses on machine learning algorithms designed to process continuous, high-velocity data flows in real-time. Students will master incremental learning techniques that operate under strict memory and computational constraints, handle concept drift, and make immediate predictions without multiple passes over the data.

Teaching Periods and Locations
27A (HAM)
Paper outline 		A Trimester :
01 Mar 2027 - 27 Jun 2027 		Hamilton 100% internal assessment

If your paper outline is not linked below, try the previous year's version of this paper.

Timetabled lectures

Note: The 2027 Timetable is not yet available.

Indicative Fees

Note: Fees for 2027 are not yet available.

Enrolling students will be sent an enrolment agreement which will confirm their fees.

There are additional fees and charges related to enrolment - please see the Table of Fees and Charges for more information.

Available subjects

Software Engineering

Artificial Intelligence

Computer Science

Electrical and Electronic Engineering

Chemical and Process Engineering

Additional information

  • Paper details current as of 11 Nov 2026 10:42pm