James Cook University Subject Handbook - 2024

CP3501 - Deep Learning

Subject Description

Deep learning has become a hot topic and emerging technology to solve complex real world problems in almost all areas. This subject enables students to explore basics and fundamentals of deep learning, to practise deep learning algorithms to solve complex problems, and to experience various tools and modules. Topics covered include: basics in deep neural networks, various deep network architectures, parameter optimisation, applications in classification, and programming with deep learning modules using Python.

Learning Outcomes

• explore the principle and theory of deep learning algorithms and models
• evaluate the efficiency and effectiveness of deep learning algorithms
• apply deep learning algorithms to solve complex real world problems
• design deep learning algorithms and solutions for an application

Subject Assessment

• Written > Examination (centrally administered) - (50%) - Individual
• Written > Project report - (25%) - Group
• Performance/Practice/Product > Practical assessment/practical skills demonstration - (25%) - 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