• Offered by Research School of Engineering
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Engineering

Data-driven decision-making is an essential component of emerging engineering systems that generate and consume very large amounts of sensing data from autonomous vehicles to digital pathology. This course covers technologies and methodologies necessary for inferring useful information and identifying underlying patterns from often raw, incomplete, noisy and corrupted data that is present in real-life engineering applications. It will also give students the opportunity to explore advanced solutions of data analytics such as sparse encoding, compressive sensing, nonlocal filtering, discriminative and generative modelling.

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Requisite and Incompatibility

To enrol in this course you must be studying Master of Engineering.

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
Band 2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2015 $3096
International fee paying students
Year Fee
2015 $4146
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery
4690 15 Feb 2016 26 Feb 2016 31 Mar 2016 27 May 2016 In Person

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