Neural Networks
for the Internet of Things

Date: On Demand

Duration: 2 Days

Course Overview

In this course learners will learn the basics of neural networks, covering both unsupervised and supervised networks. 

Course Objectives

By the end of this course learners will be able to design neural networks to learn and make predictions and decisions about IoT data.

Topics

Topics covered include unsupervised methods like Hebbian Learning, Kohonen Self Organizing Maps and K-Means Clustering, and supervised methods like the Perceptron Learning Law and Gradient Descent. Learners will also look at other forms of gradient descent, and the key issues in designing neural networks to get the best performance, including sizing the network, selecting loss and optimization methods, and overcoming under and overfitting.

Who Should Attend

IoT, Backend or Blockchain Engineer.

Prerequisites

Bachelor’s Degree in Computer Science, Electrical Engineering, with programming knowledge. Other Bachelor Degree holders who can exhibit programming experience may also be considered. Learners must complete the Neural Networks for the Internet of Things course.

Course Convener

(Click their photos to view their short biographies)

ddddd Colin Tan Keng Yan

Dr Colin Tan Keng YanDr Colin Tan Keng Yan

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 soc-ace@nus.edu.sg

To register, click Register

Course Code:
TGS-2022011564 (Classroom Learning) / TGS- 2022013115 (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