5G and Edge AI: Enabling Ultra-Low Latency Applications Training Course

This forward-looking course examines the convergence of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, adaptive, and ultra-low-latency infrastructures.

Designed for intermediate-level IT architects, this instructor-led live training (available online or onsite) enables participants to understand and design next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be equipped to:

• Grasp how 6G will reshape edge computing and IoT architectures.
• Architect distributed systems optimized for ultra-low latency, high bandwidth, and autonomous operations.
• Incorporate AI and data analytics at the edge to enable intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures prepared for 6G deployment.
• Assess the business and operational models facilitated by the integration of 6G and edge technologies.

Course Format

• Interactive lectures and group discussions.
• Case studies and practical architecture design exercises.
• Hands-on simulations using optional edge or container tools.

Customization Options

• To request a customized training program for this course, please get in touch with us to arrange your session.

This instructor-led, live training in the UAE (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 instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level developers, data scientists, and tech enthusiasts who wish to gain practical skills in deploying AI models on edge devices for various applications.

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

• Understand the principles of Edge AI and its benefits.
• 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 edge-deployed models.
• Address ethical and security considerations in Edge AI applications.

This instructor-led, live training in the UAE (online or on-site) is designed for advanced-level cybersecurity professionals, AI engineers, and IoT developers who aim to implement robust security measures and resilience strategies for Edge AI systems.

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

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

Cambricon MLUs (Machine Learning Units) are specialized AI chips designed to optimize both inference and training tasks in edge computing and data center environments.

This instructor-led live training, available online or onsite, is tailored for intermediate-level developers looking to build and deploy AI models utilizing the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be able to:

• Set up and configure development environments for both BANGPy and Neuware.
• Develop and optimize Python- and C++-based models tailored for Cambricon MLUs.
• Deploy models to edge and data center devices operating on the Neuware runtime.
• Integrate machine learning workflows with acceleration features specific to MLU.

Course Format

• Interactive lectures and discussions.
• Practical application of BANGPy and Neuware for development and deployment.
• Guided exercises focusing on optimization, integration, and testing.

Customization Options

• To arrange customized training for this course based on your specific Cambricon device model or use case, please contact us.

Huawei's Ascend CANN toolkit empowers powerful AI inference on edge devices like the Ascend 310. It provides the essential tools needed to compile, optimize, and deploy models in environments where computing power and memory are limited.

This instructor-led, live training (available online or onsite) is designed for intermediate AI developers and integrators who want to deploy and optimize models on Ascend edge devices using the CANN toolchain.

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

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Build lightweight inference pipelines using MindSpore Lite and AscendCL.
• Optimize model performance for environments with constrained compute and memory.
• Deploy and monitor AI applications in real-world edge scenarios.

Course Format

• Interactive lectures and demonstrations.
• Hands-on labs featuring edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Customization Options

• To request customized training for this course, please contact us to arrange.

This instructor-led live training in the UAE (online or onsite) is designed for beginner to intermediate-level agritech professionals, IoT specialists, and AI engineers looking 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 systems for monitoring crops and livestock.
• Create automated irrigation and environmental sensing solutions.
• Enhance agricultural efficiency through real-time Edge AI analytics.

This instructor-led live training in the UAE (online or onsite) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who aim to leverage Edge AI for innovative autonomous system solutions.

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

• Understand the role and benefits of Edge AI in autonomous systems.
• Develop and deploy AI models for real-time processing on edge devices.
• Implement Edge AI solutions in autonomous vehicles, drones, and robotics.
• Design and optimize control systems using Edge AI.
• Address ethical and regulatory considerations in autonomous AI applications.

This instructor-led, live training in the UAE (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI, from concept to practical implementation, including setup and deployment.

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

• Understand the fundamental concepts of Edge AI.
• Set up and configure Edge AI environments.
• Develop, train, and optimize Edge AI models.
• Deploy and manage Edge AI applications.
• Integrate Edge AI with existing systems and workflows.
• Address ethical considerations and best practices in Edge AI implementation.

This instructor-led, live training in the UAE (online or onsite) is designed for intermediate to advanced computer vision engineers, AI developers, and IoT professionals seeking to implement and optimize computer vision models for real-time processing on edge devices.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of Edge AI and its applications in computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Utilize frameworks such as TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimize AI models to enhance performance, power efficiency, and reduce inference latency.

This instructor-led, live training in the UAE (available online or onsite) is designed for intermediate-level finance professionals, fintech developers, and AI specialists aiming to implement Edge AI solutions in financial services.

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

• Understand the role of Edge AI in financial services.
• Implement fraud detection systems using Edge AI.
• Enhance customer service through AI-driven solutions.
• Apply Edge AI for risk management and decision-making.
• Deploy and manage Edge AI solutions in financial environments.

This instructor-led live training (the UAE / online or onsite) is tailored for intermediate-level AI developers, biomedical engineers, and healthcare professionals looking to leverage Edge AI for innovative medical solutions.

Upon completion of this training, attendees will be capable of:

• Grasping the significance and advantages of Edge AI in the healthcare sector.
• Creating and deploying AI models on edge devices tailored for healthcare use.
• Applying Edge AI solutions within diagnostic tools and wearable devices.
• Designing and implementing patient monitoring systems utilizing Edge AI.
• Navigating ethical and regulatory requirements associated with healthcare AI applications.

This instructor-led live training in the UAE (available online or onsite) is designed for intermediate-level industrial engineers, manufacturing professionals, and AI developers who aim to implement Edge AI solutions in industrial automation.

Upon completing this training, participants will be able to:

• Grasp the role of Edge AI in industrial automation.
• Implement predictive maintenance solutions leveraging Edge AI.
• Utilize AI techniques for quality control within manufacturing processes.
• Optimize industrial processes using Edge AI.
• Deploy and manage Edge AI solutions in industrial settings.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

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

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

Edge AI involves deploying artificial intelligence models directly onto devices and machinery at the network's edge, facilitating real-time decision-making with minimal latency.

This instructor-led live training (available online or onsite) targets advanced embedded and IoT professionals looking to implement AI-driven logic and control systems in manufacturing settings where speed, reliability, and offline capability are paramount.

Upon completion, participants will be able to:

• Grasp the architecture and advantages of edge AI systems.
• Develop and optimize AI models for deployment on embedded hardware.
• Utilize tools such as TensorFlow Lite and OpenVINO for low-latency inference.
• Integrate edge intelligence with sensors, actuators, and industrial protocols.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live laboratory environment.

Customization Options

• For inquiries regarding customized training for this course, please contact us to make arrangements.