DATAX504

Practical Machine Learning for Data Analysis

2027

15

500

B Trimester

Hamilton

Practical Machine Learning in Data Analysis" is a graduate-level course focused on applying machine learning methods to real-world data analysis tasks. Students will learn to preprocess data, build models, evaluate their performance, and deploy them for practical applications across diverse domains such as healthcare and finance. Emphasis is placed on practical implementation, critical evaluation, and the use of programming tools like Python or R.

Teaching Periods and Locations
27B (HAM)
Paper outline 		B Trimester :
12 Jul 2027 - 07 Nov 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.

Additional information

  • Paper details current as of 5 Nov 2026 10:39pm