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

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

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

By the end of this course, participants will be equipped to:

• Comprehend the transformative impact of 6G on 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 enable intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures ready for 6G.
• Evaluate the business and operational models facilitated by the convergence of 6G and edge technologies.

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

This instructor-led, live training in Argentina (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 Argentina (online or on-site) is designed for intermediate developers, data scientists, and technology enthusiasts seeking to acquire practical expertise in deploying AI models on edge devices across diverse applications.

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

• Grasping the foundational principles of Edge AI and its advantages.
• Establishing and configuring the edge computing infrastructure.
• Creating, training, and refining AI models for edge deployment.
• Executing practical AI solutions on edge devices.
• Assessing and enhancing the performance of models deployed at the edge.
• Navigating ethical and security challenges associated with Edge AI applications.

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

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

• Comprehend the security risks and vulnerabilities associated with Edge AI deployments.
• Deploy encryption and authentication methods to ensure data protection.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Apply secure strategies for deploying AI models in edge environments.

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

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

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on development and deployment using BANGPy and Neuware.
• Guided exercises focused on optimization, integration, and testing.

Course Customization Options

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

Huawei's Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. CANN offers the necessary tools to compile, optimize, and deploy models in environments where computational power and memory are limited.

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 completion of this training, participants will be able to:

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines utilizing MindSpore Lite and AscendCL.
• Enhance model performance for scenarios with restricted compute and memory.
• Deploy and monitor AI applications in practical edge use cases.

Course Format

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

Course Customization Options

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

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

Upon completing 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 Argentina (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 Argentina (online or onsite) is aimed at 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 Argentina (online or onsite) is designed for intermediate to advanced computer vision engineers, AI developers, and IoT professionals who aim 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 Argentina (online or onsite) targets intermediate-level finance professionals, fintech developers, and AI specialists aiming 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.
• Build fraud detection systems using Edge AI.
• Improve customer service via AI-driven solutions.
• Utilize Edge AI for risk management and decision-making.
• Deploy and manage Edge AI solutions in financial settings.

This instructor-led, live training in Argentina (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 Argentina (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 Argentina (online or onsite) targets intermediate-level developers, system architects, and industry professionals aiming to leverage Edge AI to enhance IoT applications with intelligent data processing and analytics capabilities.

By the conclusion 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 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 aiming to deploy AI-driven logic and control systems in manufacturing settings where speed, reliability, and offline operation are paramount.

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

• Grasp 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.

Course Format

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

Course Customization Options

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