Advanced Deep Learning

Dates: 20 Jul, 21 Jul 2023 | 9am-5.30pm | Online 

Duration: 2 Days

Course Overview

Recent developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders, and Deep Reinforcement Learning, are creating impressive results in a series of traditional and creative applications. For learners with basic deep learning and Python programming knowledge, it is critical to complete their knowledge towards implementation of deep learning systems in the real-world ecosystems, as well as to have more information about advanced deep learning models, how they work, what are their advantages, and applications. Again, since the implementation of robust natural language processors is one of the abilities of deep neural networks, and Natural Language Processing (NLP) has got many applications in a diverse set of businesses, practicing that application of deep learning is advisable and rational.

This module is part of Professional Certificate in Text Processing.

Course Objectives

At the completion of the course, the participants will be able to:

  • articulate advanced deep learning models, their strengths and constraints, and their applications.
  • cultivate advanced deep learning systems in different businesses.
  • Have basic skills in using deep learning algorithms to implement simple Natural Learning Processing (NLP) systems.

Who Should Attend

ICT Executives, Managers, Engineers and Analysts


Basic Deep Learning knowledge, and basic Python programming skills. Click to view the course detail of Python Programming.

Course Convener

(Click their photos to view their short biographies)

ccccc Xavier Bresson

Assoc Prof Xavier BressonAssoc Prof Xavier Bresson

Course Fees

Singapore Citizens
39 years old or younger
40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants

Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes

Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.

To enquire, email

To register, click Register

Course Codes:
TGS-2022012788 (Classroom Learning)
TGS- 2022012752 (Synchronous e-learning)

For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:

Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Strategic Tech Mgt Institute (Faculty/Department / Unit)

Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.

Course Fee Breakdown

Singapore Citizens

Singapore Citizens

39 years old or younger

Singapore Citizen

40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants

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