Skills and Technology Adoption Readiness (STAR) for Artificial Intelligence of Things (AIoT) Platform Deployment and Insights
Overview
Course Date:
TBA
Registration Period:
TBA
Duration/Frequency:
41.5 Hours
Mode of Training:
Face-to-Face (Classroom Teaching)
What You Will Learn
The Artificial Intelligence of Things (AIoT) Platform Lite course equips participants with the skills to rapidly deploy cloud-based IoT platforms that collect, analyse, and transform data into actionable insights for smarter decision-making.
Through hands-on learning, participants will explore how organisations can leverage Infrastructure as Code (IaC) technologies to automate platform deployment, connect IoT devices via the Message Queuing Telemetry Transport (MQTT) protocol, and use Python programming for data analytics and visualisation. The course provides a practical foundation for building scalable AIoT solutions that drive operational efficiency and support data-driven innovation.
By end of this course, participants will be able to:
Explain a AIoT Platform’s architecture and features.
Elaborate IaC technology and how it can deploy applications.
Apply IaC to rapidly deploy AIoT Platforms on AWS cloud.[SN5.1][Y(5.2][QK5.3]
Explain MQTT protocol, as well as its strengths and weaknesses.
Configure platforms to capture IoT data through MQTT protocol.[SN6.1][Y(6.2][QK6.3]
Create Charts and Graph to display IoT data supporting decision-making with Python programming.
Topics to be covered
Introduction to Message Queuing Telemetry Transport (MQTT) Protocol and the Artificial Intelligent of Things (AIoT) Platform Architecture
Introduction to Infrastructure as Code (IaC) and the AIoT Platform Deployment Workflow
Deployment and Configuration of AIoT Platform on Cloud
Performing Data Visualisation for Decision Making with Python Programming