HKPC Academy - Diploma in Internet of Things (IoT):Module 5: Machine learning for IoT Data
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Diploma in Internet of Things (IoT):Module 5: Machine learning for IoT Data

Programme Code 10008208-05 Subsidised by RTTP
Start Date10-10-2019
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Fannie Kwok, Tel: 27886271

Programme Info

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ObjectivWhat is Internet of Things (IoT) and why it matters?

The Internet of Things or IoT refers to the billions of physical devices around the world that are connected to the internet. As the world becomes increasingly digital, everything from coffee machines to cars are quickly becoming part of this network. Gartner forecasted that the number of connected things in use will go up to 25 billion by 2021, from 14.2 billion in 2019.
 
"The IoT will continue to deliver new opportunities for digital business innovation for the next decade, many of which will be enabled by new or improved technologies," said Nick Jones, Research Vice President at Gartner. The Internet of Things or IoT refers to the billions of physical devices around the world that are connected to the internet. As the world becomes increasingly digital, everything from coffee machines to cars are quickly becoming part of this network. Gartner forecasted that the number of connected things in use will go up to 25 billion by 2021, from 14.2 billion in 2019.
 
"The IoT will continue to deliver new opportunities for digital business innovation for the next decade, many of which will be enabled by new or improved technologies," said Nick Jones, Research Vice President at Gartner.
 
 

The Diploma in Internet of Things (IoT)

As technology develops and changes it's important to keep your skills up to date. This diploma is designed to cover IoT from technology and application point of view, through IoT hands-on workshop, to IoT platforms and machine learning of IoT data.

   
The Diploma in Internet of Things (IoT)
Course Title Duration
(Per Workshop)
Course Fee
(Per Workshop)
Module 1 Introduction to Internet of Things (IoT) – Technologies and Applications 12 hours HK$4,800
Module 2 Python for IoT – Beginner to Advanced
Module 3 IoT Sensor Do-It-Yourself (DIY) Experience Workshop
Module 4 IoT Platforms
Module 5 Machine learning for IoT Data
  • These programmes combine technical and non-technical content. Participants can make enrolments to the individual course based on their needs/ interests.
  • To attain the Diploma Certificate, participants are required to fulfil 75% attendance for all modules, i.e. module 1-5, pass the assessment and possess one of the following qualifications:
  1. be a Certificate Holder in related areas; or
  2. achieve 5 grade Es in HKCEE or equivalent; or
  3. achieve 5 Level 2s in HKCEE or equivalent; or
  4. achieve 5 Level 2s in HKDSE or equivalent; or
  5. mature student*
* 18 years old or above and with 2 years or above working experience
 
 

Introduction

This module aims to elaborate the intelligence that can be gathered by the sensing data collected through IoT sensors and platforms – with a focus on different applicable and useful machine learning models– to build smarter applications.  
 

Objectives

  • Understand different computing frameworks in an IoT solutions
  • Understand the role of machine learning to bring intelligence to the solutions
  • Understand different smart data cases
  • Understand the machine learning models in doing classification
  • Understand the machine learning models in doing regression
  • Understand how to combine different machine learning models
  • Understand the use of clustering in grouping data
  • Understand the importance of feature extraction
  • Understand how to use anomaly detection to find exceptions
  • Understand the future trend in machine learning and IoT
 

Target Audience

  • IT Managers
  • System Analysts
  • Software Architects
  • Software Developers
  • IoT Hardware Developers
  • Business Analysts
  • Data Analysts
  • Data Scientists
 

Prerequisites

It is highly recommended that participants possess basic programming knowledge (Python).
 

Course Outline

Course Outline
Day 1 Day 2
Introduction
  • Growth of IoT
  • Smart Data
 
Computing Framework
  • Fog Computing
  • Edge Computing
  • Cloud Computing
  • Distributed Computing
 
Use Case
  • Smart Energy
  • Smart Mobility
  • Smart Citizen
  • Urban Planning
  • Smart City Data Characteristics
 
Classification
  • K-nearest Neighbors
  • Naive Bayes
  • Support Vector Machine
 
Regression
  • Linear Regression
  • Support Vector Regression
Combining Models
  • Classification and Regression Trees
  • Random Forests
  • Bagging
 
Clustering
  • K-means
  • Density-based Spatial Clustering
 
Feature Extraction
  • Principal Component Analysis
  • Canonical Correlation Analysis
  • Neural Network
 
Time Series and Sequential Data
 
Anomaly Detection
  • One-class Support Vector Machine
 
Future Trends
  • IoT Data Characteristics
  • IoT Applications
  • IoT Data Analytics Algorithms
 

Course Fee

HK$4,800
 

Medium of Instruction

Cantonese, and supplemented with English for technical terms
 

Award of Certificate

Participants who have attained at least 75% attendance will be awarded a certificate of attendance issued by the Hong Kong Productivity Council.
Summer Offer

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