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James Cook University Subject Handbook - 2022

For subject information from 2025 and onwards, please visit the new JCU Course and Subject Handbook website.

MA3832 - Neural Network and Deep Learning

Credit points:03
Year:2022
Student Contribution Band:Band 1
Prerequisites:MA3405 OR MA5405 AND CP1404
Administered by:College of Science and Engineering (pre 2023 PCS)

Subject Description

    This subject in a continuation from MA3405/MA5405. In this subject, students will learn the mechanics of modern neural networks, essential skill in cloud comping and deploy the model onto cloud platform. The concepts of regularisation, pooling, optimisation momentum and convolution are introduced and applied in the field of computer vision neural networks. In this subject, Amazon is used to apply machine learning optimisation to machine learning tasks. This methodology of using machine learning for optimisation greatly enhances the outcomes of model development and removes some of the intuition needed for model development. At the conclusion of the subject, students will provide a detailed computer vision project plan using industry standard planning method.

Learning Outcomes

  • demonstrate and apply advanced theoretical and technical knowledge of neural network to an industry or research problem
  • develop multi-layer perceptron and convolution neural networks
  • programmatically interact with AWS using Python Jupyter Notebooks
  • develop and deploy machine learning models on AWS

Subject Assessment

  • Written > Essay (including multi-draft) 1 - (25%) - Individual
  • Written > Case study analysis - (25%) - Individual
  • Written > Project report - (50%) - Individual

Note that minor variations might occur due to the continuous subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.

Availabilities

Cairns, Study Period 2, Internal

Census date:Thursday, 25 Aug 2022
Study Period Dates:Monday, 25 Jul 2022 to Friday, 18 Nov 2022
Lecturer(s):
DR Usman Naseem
DR Kelly Trinh
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 26 Hours - Lectures (didactic or interactive) - May include pre-recorded content
  • 26 Hours - Workshops - May include online content

JCU Singapore, Study Period 51, Internal

Not expected to be available after this year.

Census date:Thursday, 07 Apr 2022
Study Period Dates:Monday, 14 Mar 2022 to Friday, 17 Jun 2022
Coordinator(s):
DR Kelly Trinh
Lecturer(s):
MR Chirag Desai Desai
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 26 Hours - Lectures (didactic or interactive) - May include pre-recorded content
  • 26 Hours - Workshops - May include online content

JCU Singapore, Study Period 53, Internal

Not expected to be available after this year.

Census date:Thursday, 01 Dec 2022
Study Period Dates:Monday, 07 Nov 2022 to Friday, 17 Feb 2023
Coordinator(s):
DR Kelly Trinh
Lecturer(s):
DR Randy Zhu
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 26 Hours - Lectures (didactic or interactive) - May include pre-recorded content
  • 26 Hours - Workshops - May include online content

Townsville, Study Period 2, Internal

Census date:Thursday, 25 Aug 2022
Study Period Dates:Monday, 25 Jul 2022 to Friday, 18 Nov 2022
Lecturer(s):
DR Usman Naseem
DR Kelly Trinh
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 26 Hours - Lectures (didactic or interactive) - May include pre-recorded content
  • 26 Hours - Workshops - May include online content