As the world becomes increasingly digital, everything from coffee machines to cars can quickly become part of IoT network.
The IoT will continue to deliver new opportunities for digital business innovation for the next decade.
This technical course aims at elaborating the intelligence gathered by the sensing data through IoT sensors and platforms – with a focus on different applicable and useful machine learning models to build smarter applications.
- Growth of IoT
- Smart Data
- Fog Computing
- Edge Computing
- Cloud Computing
- Distributed Computing
- Smart Energy
- Smart Mobility
- Smart Citizen
- Urban Planning
- Smart City Data Characteristics
- K-nearest Neighbors
- Naive Bayes
- Support Vector Machine
- Linear Regression
- Support Vector Regression
- Classification and Regression Trees
- Random Forests
- Density-based Spatial Clustering
- Principal Component Analysis
- Canonical Correlation Analysis
- Neural Network
Time Series and Sequential Data
- One-class Support Vector Machine
- IoT Data Characteristics
- IoT Applications
- IoT Data Analytics Algorithms
Simon MOK is an IT professional trainer with over 10 years of experience, specialised in IoT, data analytics, AI and machine learning and programing. He has rich experience in leading development team to deliver software solutions for clients. He is a M.Phil from the University of Hong Kong and MSc in Computer Science from the Chinese University of Hong Kong.
12, 19 Dec 2020 (Sat)
09:30 – 17:00
Total 14 training hours
Cantonese, supplemented with English terminology
HK$4,800 (up to HK$3,200* subsidy)
* Maximum saving, with the final grant subjects to approval.
This course is subject to approval under the Reindustrialisation and Technology Training Programme (RTTP) with up to 2/3 course fee reimbursement upon successful applications. For details: https://rttp.vtc.edu.hk.
Award of Certificate of Attendance
Participants with full Attendance will be awarded a Certificate of Attendance issued by the Hong Kong Productivity Council.
It is highly recommended that participants possess basic programming knowledge (Python)
**Bring Your Own Device (BYOD): Windows 7/10 / Mac OS 10.x or above with minimum 2 GB RAM and 20 GB hard disk