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Advanced Machine Learning:
Deep Learning

Date: TBA

Duration: 1 Day

Harness and apply deep learning techniques in a variety of business settings

Course Overview

The application of machine learning is deepening and widening in the world of business and technology. Among different machine learning algorithms, deep learning stands out. Since its introduction in 2006, deep learning has fulfilled some of the oldest artificial intelligence promises, such as autonomous/driverless vehicles, machine translation, precise and speaker-independent speech recognition, and robust visual object recognition. Deep learning systems have even beaten the human experts in their field and achieved remarkable performances.

In this course, we will address the what, why and how of deep learning. What is deep learning? Why do we need deep learning? And how do we apply and harness the benefits of deep learning in business cases? We will focus on the three popular deep learning algorithms, namely Convolutional Neural Networks (CNN), Long/Short Term Memories (LSTM), and Generative Adversarial Networks (GAN), and their applications. The methods and platforms for implementation and evaluation of deep learning systems would be discussed. Furthermore, learners will practise employing deep learning to deal with a few applied examples using Python and Octave environments.

Course Objectives

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

  • Articulate an efficient procedure of implementation and evaluation of deep learning models.
  • Understand the basic definitions and applications of CNN, LSTM, and GAN.
  • Define the business case for a deep learning approach.
  • Demonstrate an understanding of the practical aspects of deep learning, its platforms and tools.
  • Solve authentic business problems with deep learning models.

Who Should Attend

IT Engineers, IT Consultants, IT Managers, Technology Managers, Business Managers

Prerequisites

Basic knowledge of machine learning and Python programming

Facilitators

(Click their photos to view their short biographies)

Dr Amirhassan MonajemiDr Amirhassan Monajemi

Dr Edmund LowDr Edmund Low

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.

NTUC members enjoy 50% unfunded course fee support for up to $250 each year (or up to $500 for NTUC members aged 40 years old and above) when you sign up for courses supported under UTAP (Union Training Assistance Programme). Please visit e2i’s website to find out more.

To enquire, email soc-ace@nus.edu.sg

To register, click Register

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