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Short Course

Advanced Deep Learning

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
20 Jun, 21 Jun 2024 | 9am – 5.30pm2Synchronous e-LearningTGS-2022012752

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.

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.

Prerequisites

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

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This programme is part of

  • Professional Certificate in Text Processing

    • Types of Available Fundings

  • SkillsFuture Credit
  • UTAP
  • PSEA
  • Enhanced Training Support
  • SFEC

    • Instructors


    A/Prof Xavier Bresson

    A/Prof Xavier Bresson

    A/Prof Xavier Bresson is an international leader in the field of deep learning. Particularly, he co-pioneered a new machine learning technology called graph neural networks (GNN), which combines graph theory and neural network techniques to tackle complex data domains. He has organised several international conferences and tutorials on graph deep learning such as the recent UCLA’21 workshop on “Deep Learning and Combinatorial Optimization”, the MLSys’21 workshop on “Graph Neural Networks and Systems”, the UCLA’19 workshop on “New Deep Learning Techniques”, and the NeurIPS’17, CVPR’17 and SIAM’18 tutorials on “Geometric Deep Learning on Graphs and Manifolds”. He has been a speaker at the top machine learning conferences KDD’21, AAAI’21, ICLR’20 and ICML’20. In 2002, he co-developed with Turing award winner Yoshua Bengio a new class of expressive GNN. He has published more than 70 peer-reviewed articles, which have been cited 13,500+. A/Prof Bresson has been the main lecturer of undergraduate deep learning courses since 2015 at EPFL, NTU and NUS, and has received outstanding evaluations for his teaching material and engaging style. He has also taught graduate courses on advanced deep learning at NUS and was a guest lecturer for Turing award winner Yann LeCun’s course at NYU. He has provided industrial short courses on AI and Deep Learning to Fortune 500 companies s.a. Deloitte, UnitedHealth and university alumni training centres at UCLA, EPFL, and NTU.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Programme Fee S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00
    Less: SSG Grant Amount S$1,470.00 S$1,470.00 S$1,470.00 S$1,470.00 -
    Nett Programme Fee S$630.00 S$630.00 S$630.00 S$630.00 S$2,100.00
    9% GST on Nett Programme Fee S$56.70 S$56.70 S$56.70 S$56.70 S$189.00
    Total Nett Programme Fee Payable, Including GST S$686.70 S$686.70 S$686.70 S$686.70 S$2,289.00
    Less Additional Funding - S$420.00 - S$420.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$686.70 S$266.70 S$686.70 S$266.70 S$2,289.00
    1. Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
    2. GST shall apply at prevailing rates.
    3. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.

    Other Information

    This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

    Connect with us

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Telephone: +65 6516 5523
    Email: soc-ace@nus.edu.sg

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