COURSE INTRODUCTION
This programme introduces how connected devices, sensors and industrial data can be combined with AI-supported analytics to improve visibility and decision-making. Participants explore IoT architecture, data collection, connectivity, analytics and optimisation concepts, with emphasis on practical opportunities for monitoring and improving real operational processes. Practical examples and guided discussion help participants connect the subject to decisions and challenges in their own workplace.
COURSE OBJECTIVES
By the end of this programme, participants should be able to:
- Explain the core concepts, terminology and working principles related to Internet of Things (IOT) - With AI Data Analytics & Optimization.
- Apply structured methods and industry good practices for Architecture of the Internet of Things, IoT components, devices, hardware and software requirements, and IoT embedded systems, microcontrollers and sensors.
- Evaluate relevant automation & digital situations and identify risks, gaps and improvement opportunities.
- Translate the learning into practical workplace actions and sound technical decisions.
COURSE OUTCOME
Upon completion, participants will be better prepared to:
- Assess relevant workplace situations using the concepts and methods covered in Internet of Things (IOT) - With AI Data Analytics & Optimization.
- Select and apply appropriate tools, checks or controls for Architecture of the Internet of Things, IoT components, devices, hardware and software requirements, and IoT embedded systems, microcontrollers and sensors.
- Recommend actions that support industrial control, diagnostics, data use and implementation capability.
- Communicate findings, improvement opportunities and next steps clearly to relevant stakeholders.
WHO SHOULD ATTEND
This programme is suitable for software developers, solution and technical architects, process engineers, data analysts, students, managers and professionals who want to apply IoT, connected-device data and AI-supported analytics.
COURSE CONTENT
- Architecture of the Internet of Things
- IoT components, devices, hardware and software requirements
- IoT embedded systems, microcontrollers and sensors
- Raspberry Pi interfaces and IoT communication protocols
- Big Data, data management and Data Analytics
- Programming, security, testing and compliance for IoT systems
- AI deployment on sensor data for analytics and optimization
- Practical IoT applications for smart factories, energy and smart homes
