Statistical Models
for the Internet of Things

Date: On Demand

Duration: 2 Days

Course Overview

In this course learners will look at the various statistical methods that can be used to process IoT data in order to make predictions or to make diagnoses on the data. 

This module is part of Professional Certification in Deep Learning for the Internet of Things.

Course Objectives

By the end of this course learners will be able to apply simple statistical methods to analyzing and understanding IoT data to make predictions and diagnoses.

Topics

Topics covered include:

  • Autoregressive Moving Average (ARMA)
  • Autoregressive Integrated Moving Average (ARIMA) models
  • Simple linear regression
  • Multivariate linear regression
  • Nonlinear regression
  • Bayesian models
  • Decision Trees
  • Support Vector Machines

Who Should Attend

IoT, Backend or Blockchain Engineer

Prerequisites

Bachelor’s Degree in Computing or Mathematics, with programming knowledge. Other Bachelor’s Degree holders with programming knowledge may be considered. Learners should have taken the set of three courses for the Professional Certification in Cloud Technologies for the Internet of Things.

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-2022011563 (Classroom Learning) / TGS-022013108 (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

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