Deep Learning for the Internet of Things

Dates: 7 Mar, 8 Mar 2024 | 9am-5.30pm | Classroom Learning 

Duration: 2 Days

Course Overview

In this course learners will learn about deep learning technologies and their usage in IoT. Topics covered include the limitations of neural networks and the motivation behind deep learning, handling time series with long-short term memories, autoregressive networks, generative adversarial networks, convolutational neural networks, and object tracking networks like YOLO and SSD. Learners will also look at how to compose multiple network architectures.

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

Course Objectives

By the end of this course learners will be able to design and build sophisticated deep learning neural networks to analyze, understand and react to IoT data.

Who Should Attend

IoT, Backend or 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 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

GST shall apply at prevailing rates.

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 Codes:
TGS-2022013118 (Classroom Learning)
TGS-2022013104 (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

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