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

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

Designed for intermediate IT architects, this instructor-led training (available online or onsite) focuses on understanding and designing next-generation distributed architectures that leverage the combined power of 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Comprehend how 6G will reshape edge computing and IoT architectures.
• Architect distributed systems optimized for ultra-low latency, high bandwidth, and autonomous operations.
• Implement AI and data analytics at the edge to enable intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures ready for 6G adoption.
• Assess the business and operational models facilitated by the 6G-edge convergence.

Course Format

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

Customization Options

• To arrange customized training for this course, please contact us to discuss your specific needs.

This instructor-led live training in Turkey (online or onsite) targets 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.

Upon completing this training, participants will be capable of:

• Exploring advanced techniques in Edge AI model development and optimization.
• Implementing cutting-edge strategies for deploying AI models on edge devices.
• Utilizing specialized tools and frameworks for advanced Edge AI applications.
• Optimizing the performance and efficiency of Edge AI solutions.
• Investigating innovative use cases and emerging trends in Edge AI.
• Addressing advanced ethical and security considerations in Edge AI deployments.

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

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

• Understand the fundamental principles and benefits of Edge AI.
• 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 Turkey (online or onsite) 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 end of this training, participants will be able to:

• Comprehend the security risks and vulnerabilities associated with Edge AI deployments.
• Deploy encryption and authentication techniques to ensure data protection.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Execute secure AI model deployment strategies within edge environments.

Cambricon MLUs (Machine Learning Units) are specialized AI processors designed for optimized inference and training in both edge and datacenter environments.

This instructor-led live training (available online or on-site) is designed for intermediate 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 development environments for BANGPy and Neuware.
• Develop and optimize Python and C++ based models for Cambricon MLUs.
• Deploy models to edge and datacenter 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 focusing on optimization, integration, and testing.

Course Customization Options

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

Huawei's Ascend CANN toolkit empowers powerful AI inference on edge devices like the Ascend 310. It provides crucial tools for compiling, optimizing, and deploying models in environments with limited compute and memory capacity.

This instructor-led, live training (available online or onsite) targets intermediate 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 able to:

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines utilizing MindSpore Lite and AscendCL.
• Optimize model performance within constrained compute and memory settings.
• 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.

Course Customization Options

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

This instructor-led, live training in Turkey (online or on-site) is aimed at 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 Turkey (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 Turkey (online or onsite) is designed for intermediate-level developers and IT professionals seeking a comprehensive grasp of Edge AI, ranging from conceptual foundations to practical implementation, including setup and deployment.

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

• Grasping the core principles of Edge AI.
• Establishing and configuring Edge AI workspaces.
• Creating, training, and refining Edge AI models.
• Deploying and overseeing Edge AI applications.
• Incorporating Edge AI into current systems and workflows.
• Navigating ethical implications and adhering to best practices in Edge AI deployment.

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate to advanced computer vision engineers, AI developers, and IoT professionals who want 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 for performance, power efficiency, and low-latency inference.

This instructor-led, live training in Turkey (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.

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 in Turkey (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 Turkey (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 Turkey (online or onsite) is tailored for intermediate-level developers, system architects, and industry professionals seeking to leverage Edge AI to enhance IoT applications with intelligent data processing and analytics capabilities.

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

• Grasping the fundamentals of Edge AI and its role in IoT.
• Setting up and configuring Edge AI environments for IoT devices.
• Developing and deploying AI models on edge devices for IoT solutions.
• Implementing real-time data processing and decision-making capabilities in IoT systems.
• Integrating Edge AI with various IoT protocols and platforms.
• Addressing ethical considerations and adhering to best practices for Edge AI in 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 implement AI-driven logic and control systems in manufacturing environments where speed, reliability, and offline operation are essential.

Upon completion of 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 for low-latency inference.
• Integrate edge intelligence with sensors, actuators, and industrial protocols.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

• For a customized training version of this course, please reach out to us to make arrangements.