CANN for Edge AI Deployment Training Course

This instructor-led, live training in Greece (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists keen to explore how 5G networks accelerate Edge AI applications.

By the conclusion of this training, participants will be able to:

• Grasp the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimised for low-latency applications within 5G environments.
• Implement real-time decision-making systems using Edge AI and 5G connectivity.
• Optimise AI workloads for efficient performance on edge devices.

This 21-hour training in Greece equips IT architects with the expertise to design next-generation distributed systems. Discover how 6G, edge computing, and AI integration create low-latency, scalable infrastructures. Develop practical skills to build secure, resilient, and intelligent edge architectures that meet future business requirements.

This instructor-led, live training in Greece (online or onsite) is aimed at advanced-level AI practitioners, researchers, and developers who wish to master the latest advancements in Edge AI, optimize their AI models for edge deployment, and explore specialized applications across various industries.

By the end of this training, participants will be able to:

• Explore advanced techniques in Edge AI model development and optimization.
• Implement cutting-edge strategies for deploying AI models on edge devices.
• Utilize specialized tools and frameworks for advanced Edge AI applications.
• Optimize performance and efficiency of Edge AI solutions.
• Explore innovative use cases and emerging trends in Edge AI.
• Address advanced ethical and security considerations in Edge AI deployments.

This live instructor-led training in Greece, available online or onsite, targets intermediate developers, data scientists, and tech enthusiasts seeking to develop practical competencies in deploying AI models on edge devices for diverse applications.

By the conclusion of the program, participants will be able to:

• Understand the fundamental principles of Edge AI and its advantages.
• Set up and configure the edge computing environment.
• Develop, train, and optimize AI models for edge deployment.
• Implement practical AI solutions on edge devices.
• Evaluate and improve the performance of models deployed on the edge.
• Address ethical and security considerations in Edge AI applications.

This instructor-led, live training in Greece (online or onsite) is aimed at advanced-level cybersecurity professionals, AI engineers, and IoT developers who wish to implement robust security measures and resilience strategies for Edge AI systems.

By the end of this training, participants will be able to:

• Understand security risks and vulnerabilities in Edge AI deployments.
• Implement encryption and authentication techniques for data protection.
• Design resilient Edge AI architectures that can withstand cyber threats.
• Apply secure AI model deployment strategies in edge environments.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills to optimize AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Greece (online or on-site) is aimed at beginner to intermediate agritech professionals, IoT specialists, and AI engineers who wish to develop and deploy Edge AI solutions for smart farming.

Upon completion of this training, participants will be able to:

• Grasp the role of Edge AI in precision agriculture.
• Deploy AI-driven monitoring systems for crops and livestock.
• Create automated irrigation and environmental sensing solutions.
• Enhance agricultural efficiency through real-time Edge AI analytics.