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CP3501 - Deep Learning

[Not offered in 2023]

Credit points: 3
Year: 2023
Student Contribution Band: Band 2
Administered by: College of Science and Engineering

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: 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.