Neural Networks
for the Internet of Things

Dates: 29 Feb, 1 Mar 2024 | 9am-5.30pm | Classroom Learning 

Duration: 2 Days

Course Overview

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

This course is part of Professional Certificate in Deep Learning for IoT.

Course Objectives

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

Who Should Attend

IoT, backend and blockchain engineers.

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 photo to view biography)

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

GST shall apply at prevailing rates.

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

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.

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

To register, click Register

Course Codes
TGS-2022011564 (Classroom Learning)
TGS- 2022013115 (Synchronous e-learning)

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