COMPX523
Machine Learning for Data Streams
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
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27A (HAM)
Hamilton, In-person27A (HAM)A Trimester :01 Mar 2027 - 27 Jun 2027HamiltonPaper outline100% internal assessment
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27A (HAM) Paper outline |
A Trimester : 01 Mar 2027 - 27 Jun 2027 |
Hamilton |
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100% internal assessment |
If your paper outline is not linked below, try the previous year's version of this paper.
Indicative Fees
You will be sent an enrolment agreement which will confirm your fees. Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment - please see the Table of Fees and Charges for more information.
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You will be sent an enrolment agreement which will confirm your fees. Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment - please see the Table of Fees and Charges for more information.
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You will be sent an enrolment agreement which will confirm your fees. Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment - please see the Table of Fees and Charges for more information.
Available subjects
Additional information
- Paper details current as of 8 Aug 2026 01:05am
- Indicative fees current as of 11 Aug 2026 01:20am