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

6G and the Intelligent Edge is a forward-thinking course that investigates the convergence of 6G wireless technologies with edge computing, IoT ecosystems, and AI-powered data processing to enable intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available online or onsite) targets intermediate-level IT architects looking to understand and design next-generation distributed architectures by leveraging the synergy between 6G connectivity and intelligent edge systems.

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

• Grasp how 6G will reshape edge computing and IoT architectures.
• Design distributed systems supporting 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 infrastructures prepared for 6G.
• Evaluate business and operational models enabled by the convergence of 6G and edge technologies.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Czech Republic (online or onsite) targets advanced-level AI practitioners, researchers, and developers aiming to master recent advancements in Edge AI, optimize their AI models for edge deployment, and explore specialized applications across diverse industries.

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

• Investigate advanced techniques for developing and optimizing Edge AI models.
• Apply modern strategies for deploying AI models on edge devices.
• Leverage specialized tools and frameworks for advanced Edge AI applications.
• Enhance the performance and efficiency of Edge AI solutions.
• Discover innovative use cases and emerging trends in Edge AI.
• Tackle advanced ethical and security challenges in Edge AI deployments.

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

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

• Grasp the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to safeguard data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Deploy AI models securely within edge environments.

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

This instructor-led live training session (available online or onsite) targets intermediate-level developers who want to build and deploy AI models leveraging the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be able to:

• Set up and configure the development environment for BANGPy and Neuware.
• Develop and optimize Python- and C++-based models specifically for Cambricon MLUs.
• Deploy models to edge devices and data centers running the Neuware runtime.
• Integrate machine learning workflows with MLU-specific acceleration features.

Course Format

• Interactive lectures and discussions.
• Practical, hands-on development and deployment using BANGPy and Neuware.
• Guided exercises concentrating on optimization, integration, and testing.

Customization Options

• To arrange customized training tailored to your specific Cambricon device model or use case, please contact us.

The Huawei Ascend CANN toolkit empowers powerful AI inference on edge devices, such as the Ascend 310. It provides essential tools for compiling, optimizing, and deploying models in environments with constrained compute and memory resources.

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

Upon completing this training, participants will be able to:

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

Course Format

• Interactive lectures and demonstrations.
• Hands-on lab exercises 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 it.

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

This instructor-led, live training in Czech Republic (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 Czech Republic (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 Czech Republic (online or onsite) is aimed at intermediate-level to advanced-level 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 Czech Republic (online or onsite) is aimed at intermediate-level finance professionals, fintech developers, and AI specialists who wish to implement Edge AI solutions in financial services.

Upon completing this training, participants will be able to:

• Grasp the role of Edge AI in financial services.
• Deploy fraud detection systems using Edge AI.
• Improve customer service via 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 in Czech Republic (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for innovative healthcare solutions.

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

• Understand the role and benefits of Edge AI in healthcare.
• Develop and deploy AI models on edge devices for healthcare applications.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems using Edge AI.
• Address ethical and regulatory considerations in healthcare AI applications.

This instructor-led live training in Czech Republic (online or onsite) targets intermediate-level industrial engineers, manufacturing professionals, and AI developers aiming 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 Czech Republic (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 on 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) is designed for advanced-level embedded and IoT professionals aiming to implement AI-driven logic and control systems within manufacturing settings where speed, reliability, and offline functionality are paramount.

Upon completing this training, participants will be able to:

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

Course Format

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

Course Customization Options

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