Industrial Edge AI Training is a focused two-day program designed to help professionals understand how deploying artificial intelligence at the edge transforms industrial automation. This course explores how Edge AI enables real-time decision-making, predictive control, quality inspection, and intelligent automation directly on industrial devices, improving efficiency, reliability, safety, and scalability across manufacturing and industrial operations.

• Understand Industrial Edge AI concepts
• Learn smart manufacturing fundamentals
• Understand real-time industrial processing
• Gain knowledge of AI-driven automation
• Learn predictive maintenance basics
• Understand industrial IoT integration
• Explore edge-based monitoring systems
• Identify industrial AI use cases

• Industrial automation and control engineers
• Manufacturing and plant operations professionals
• AI and data science professionals in industrial domains
• IoT, embedded systems, and edge computing engineers
• Industry 4.0 and digital transformation leaders

• Basic understanding of industrial automation or manufacturing processes
• Familiarity with sensors, PLCs, SCADA, or industrial control systems
• General awareness of artificial intelligence or data analytics
• Interest in real-time and intelligent industrial systems

• Understanding Edge AI concepts for industrial automation
• Awareness of deploying AI models on industrial edge devices
• Knowledge of real-time monitoring and control using AI
• Evaluating safety, reliability, and performance trade-offs
• Interpreting real-world industrial Edge AI use cases

By the end of this training, participants will be able to explain how Edge AI is applied in industrial automation, understand deployment and optimization of AI models on industrial edge devices, evaluate safety and reliability considerations, and assess how Edge AI improves efficiency, quality, and decision-making in industrial environments.

Introduction to Edge AI in Industrial Automation
• Definition and scope of Edge AI in industrial environments
• Difference between cloud-based analytics and Edge AI systems
• Benefits of low latency, reliability, and on-device intelligence
• Overview of industrial Edge AI use cases

Industrial Edge Architecture and Devices
• Industrial sensors, controllers, and edge gateways
• Edge hardware platforms and AI accelerators
• Data flow between machines, edge, and enterprise systems
• Infrastructure and deployment considerations

AI Models for Industrial Edge Applications
• Selecting models suitable for industrial environments
• Trade-offs between accuracy, latency, and robustness
• Computer vision for quality inspection
• Time-series and anomaly detection models

Model Optimization and Deployment
• Model compression and optimization concepts
• Deployment pipelines for industrial edge AI
• Updating and managing models in production environments
• Monitoring performance and operational health

Safety, Security, and Reliability
• Safety-critical considerations in industrial AI systems
• Cybersecurity and data protection at the edge
• Fault tolerance and fail-safe mechanisms
• Compliance with industrial standards and regulations

Industrial Use Cases and Future Trends
• Predictive maintenance and condition monitoring
• Intelligent quality inspection and defect detection
• Autonomous and adaptive production systems
• Future directions of Edge AI in Industry 4.0

• Industrial Edge AI fundamentals
• Smart factory concepts
• Real-time industrial analytics
• Predictive maintenance techniques
• Industrial IoT and edge systems
• AI-driven automation workflows
• Monitoring and control systems
• Computer vision in manufacturing
• Industrial security considerations
• Practical industrial AI scenarios

• Conceptual understanding assessments
• Industrial automation use case analysis exercises
• Safety and reliability evaluation activity
• Final knowledge evaluation quiz

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in Industrial Edge AI Training, validating their expertise in applying Edge AI concepts to industrial automation, real-time intelligence, and smart manufacturing systems.