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

The '6G and the Intelligent Edge' course offers a forward-looking perspective on how 6G wireless technologies merge with edge computing, IoT ecosystems, and AI-driven data processing to create intelligent, adaptive infrastructures with ultra-low latency.

This instructor-led live training, available both online and onsite, is tailored for intermediate-level IT architects aiming to grasp and design next-generation distributed architectures that harness the synergy between 6G connectivity and intelligent edge systems.

After completing this course, participants will be equipped to:

• Comprehend how 6G will reshape edge computing and IoT architectures.
• Design distributed systems capable of ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge to facilitate intelligent decision-making.
• Plan scalable, secure, and resilient edge infrastructures ready for 6G.
• Evaluate the business and operational models empowered by the convergence of 6G and edge technologies.

Course Format

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

Customization Options

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

This instructor-led live training in India (online or on-site) is designed for advanced-level AI practitioners, researchers, and developers who aim to master the latest Edge AI advancements, optimize their models for edge deployment, and explore specialized applications across various sectors.

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

• Investigate advanced methods for developing and optimizing Edge AI models.
• Apply cutting-edge strategies for deploying AI models on edge devices.
• Leverage specialized tools and frameworks for complex Edge AI applications.
• Enhance the performance and efficiency of Edge AI solutions.
• Explore innovative use cases and emerging trends in the Edge AI landscape.
• Tackle advanced ethical and security challenges associated with Edge AI deployments.

This instructor-led live training in India (online or onsite) targets intermediate-level developers, data scientists, and tech enthusiasts seeking practical skills in deploying AI models on edge devices for diverse applications.

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

• Comprehend the core principles of Edge AI and its advantages.
• Establish and configure the edge computing environment.
• Develop, train, and optimize AI models specifically for edge deployment.
• Deploy practical AI solutions on edge devices.
• Assess and enhance the performance of models deployed on the edge.
• Tackle ethical and security issues inherent in Edge AI applications.

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

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

• Grasp the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to protect data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Deploy secure AI models within 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 either online or on-site, targets intermediate-level developers who aim to construct and deploy AI models leveraging the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

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

• Establish and configure the development environments for BANGPy and Neuware.
• Create and optimize models using Python and C++ specifically for Cambricon MLUs.
• Deploy models onto edge and data center devices operating on the Neuware runtime.
• Integrate machine learning workflows with acceleration capabilities specific to MLUs.

Course Format

• Engaging lectures paired with interactive discussions.
• Practical, hands-on sessions involving development and deployment with BANGPy and Neuware.
• Guided exercises concentrating on optimization, integration, and testing.

Customization Options for the Course

• If you require customized training tailored to your specific Cambricon device model or use case, please get in touch with us to make the necessary arrangements.

The Huawei Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. It offers critical tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

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

Upon completing this training, participants will be equipped to:

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines leveraging MindSpore Lite and AscendCL.
• Enhance model performance in environments with restricted compute and memory.
• Deploy and monitor AI applications in practical, real-world edge scenarios.

Format of the Course

• Interactive lectures and demonstrations.
• Practical lab sessions focusing on edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Course Customization Options

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

This instructor-led, live training in India (online or onsite) is designed for beginner to intermediate-level agritech professionals, IoT specialists, and AI engineers who wish to develop and deploy Edge AI solutions for smart farming.

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

• Understand the role of Edge AI in precision agriculture.
• Implement AI-driven crop and livestock monitoring systems.
• Develop automated irrigation and environmental sensing solutions.
• Optimize agricultural efficiency using real-time Edge AI analytics.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who wish 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 India (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI, covering everything from the initial concept to practical implementation, including setup and deployment.

Upon completing this training, participants will be able to:

• Grasp 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 adhere to best practices in Edge AI implementation.

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

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

• Understand 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.
• Use frameworks like TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimize AI models for performance, power efficiency, and low-latency inference.

This instructor-led, live training in India (online or onsite) targets intermediate-level finance professionals, fintech developers, and AI specialists who aim to implement Edge AI solutions in financial services.

By the conclusion 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 live, instructor-led training in India (online or onsite) targets intermediate-level healthcare professionals, biomedical engineers, and AI developers who want to leverage Edge AI for innovative healthcare solutions.

Upon completing this training, participants will be able to:

• Grasp the role and advantages of Edge AI in the healthcare sector.
• Build and deploy AI models on edge devices for healthcare use cases.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems leveraging Edge AI.
• Navigate ethical and regulatory considerations in healthcare AI applications.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level industrial engineers, manufacturing professionals, and AI developers who wish to implement Edge AI solutions in industrial automation.

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

• Understand the role of Edge AI in industrial automation.
• Implement predictive maintenance solutions using Edge AI.
• Apply AI techniques for quality control in manufacturing processes.
• Optimize industrial processes using Edge AI.
• Deploy and manage Edge AI solutions in industrial environments.

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

By the conclusion of this training, participants will be equipped 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 machines at the network's edge, facilitating real-time decision-making with minimal latency.

This instructor-led, live training (available online or onsite) is designed for advanced-level embedded and IoT professionals who aim to deploy AI-powered logic and control systems within manufacturing environments where speed, reliability, and offline operation are paramount.

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

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

Format of the Course

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

Course Customization Options

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