- Code ENGN8535
- Unit Value 6 units
- Offered by School of Engineering
- ANU College ANU College of Engineering Computing & Cybernetics
- Course subject Engineering
- Areas of interest Statistics, Algorithms and Data, Artifical Intelligence
- Academic career PGRD
- Dr Tim Molloy
- Mode of delivery In Person
First Semester 2023
See Future Offerings
In 2023, this course is on campus with remote adjustments only for participants with unavoidable travel restrictions/visa delays.
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 applications. It will also give students the opportunity to explore advanced solutions of data analytics such as dimensionality reduction, sparse encoding, compressive sensing, nonlinear filtering, manifold learning, and generative data modelling.
Upon successful completion, students will have the knowledge and skills to:
- Describe a number of models for inference from data
- Assess the strength and weakness of each of these models
- Interpret the mathematical equations from Linear Algebra, Statistics, and Probability Theory used in the learning models
- Implement efficient data analysis algorithms on a computer
- Design test procedures in order to evaluate a model
- Combine several models in order to gain better results
- Assignments (45) [LO null]
- Mid-Term Quiz (25) [LO null]
- Final Exam (30) [LO null]
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12 x 2 hr Lectures
12 x1 hr Tutorial
Requisite and Incompatibility
"Element of statistical machine Learning"
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|2660||20 Feb 2023||27 Feb 2023||31 Mar 2023||26 May 2023||In Person||N/A|