CODE: AI19
DURATION: 3 Days/5 Days/10 Days
CERTIFICATIONS: CPD
As billions of devices connect to the internet, traditional cloud-only architectures are no longer sufficient for applications requiring real-time processing, low latency, and bandwidth efficiency. This course provides a comprehensive foundation in edge computing and IoT integration, teaching participants to design, deploy, and manage distributed systems where computation happens closer to data sources. Through practical tasks, participants will learn to build responsive, reliable, and secure intelligent systems that leverage both edge and cloud resources effectively.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Design and implement edge computing architectures for real-time IoT applications.
Deploy and manage containerized workloads on edge devices and gateways.
Process and analyze sensor data streams at the edge with low latency.
Implement secure device provisioning, authentication, and communication.
Develop hybrid edge-cloud data pipelines and analytics systems.
Apply ML inference at the edge for immediate decision-making.
Monitor, maintain, and update distributed edge systems reliably.
At the end of this course, you’ll understand:
This course is ideal for IoT engineers, edge computing specialists, system architects, embedded systems developers, and cloud engineers involved in designing or managing connected devices. It also suits data engineers, software developers, IT managers, and technical leaders who want practical skills in integrating IoT devices with edge and cloud architectures for real-time analytics, automation, and intelligent decision-making.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
