Edge AI for Agriculture: Smart Farming and Precision Monitoring Training Course

This instructor-led, live training in Vietnam (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists who want to explore how 5G networks accelerate Edge AI applications.

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

• Grasp the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimized for low-latency applications within 5G environments.
• Implement real-time decision-making systems leveraging Edge AI and 5G connectivity.
• Optimize AI workloads for efficient performance on edge devices.

"6G and the Intelligent Edge" is a forward-looking course that explores the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to support intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT architects who wish to understand and design next-generation distributed architectures leveraging the synergy of 6G connectivity and intelligent edge systems.

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

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

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation with 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 Vietnam (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.

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

• Investigate advanced techniques for developing and optimizing Edge AI models.
• Apply cutting-edge strategies for deploying AI models on edge devices.
• Utilize 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.
• Address advanced ethical and security considerations in Edge AI deployments.

This live, instructor-led training in Vietnam (online or onsite) is designed for intermediate developers, data scientists, and technology enthusiasts aiming to acquire practical skills in deploying AI models on edge devices for diverse applications.

By the end 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 Vietnam (online or onsite) is designed for advanced-level cybersecurity experts, AI engineers, and IoT developers who aim to implement strong security measures and resilience strategies for Edge AI systems.

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

• Analyze security risks and vulnerabilities in Edge AI deployments.
• Implement encryption and authentication techniques to ensure data protection.
• Design resilient Edge AI architectures 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 high-performance inference and training in both edge computing and data center environments.

This instructor-led, live training session (available online or onsite) is tailored for intermediate-level developers looking to build and deploy AI models using 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 BANGPy and Neuware.
• Develop and optimize models written in Python and C++ for Cambricon MLUs.
• Deploy models to edge devices and data centers running the Neuware runtime.
• Integrate machine learning workflows with specific MLU acceleration features.

Course Format

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

Customization Options

• To request a customized version of this course tailored to your specific Cambricon device model or use case, please contact us to arrange.

The Ascend CANN toolkit from Huawei facilitates robust AI inference on edge hardware, including the Ascend 310. This toolkit offers critical utilities for compiling, optimizing, and deploying machine learning models in environments where computational power and memory are limited.

This instructor-led live training, available online or in-person, targets intermediate AI developers and integrators looking to deploy and optimize their models on Ascend edge devices using the CANN toolchain.

Upon completing this course, participants will be capable of:

• Preparing and converting AI models for the Ascend 310 using CANN utilities.
• Constructing efficient inference pipelines utilizing MindSpore Lite and AscendCL.
• Enhancing model performance within constrained compute and memory settings.
• Deploying and monitoring AI applications in practical edge scenarios.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical lab exercises featuring edge-specific models and scenarios.
• Live deployment demonstrations on both virtual and physical edge hardware.

Customization Options

• For tailored training options, please contact us to make arrangements.

This instructor-led, live training Vietnam (online or onsite) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who want to harness Edge AI for cutting-edge autonomous system solutions.

By the end of this course, 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 Vietnam (online or onsite) is designed for intermediate-level developers and IT professionals who want to gain a thorough understanding of Edge AI, ranging from foundational concepts 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.
• Create, 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 Vietnam (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 Vietnam (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.
• Implement fraud detection systems utilizing Edge AI.
• Enhance customer service through AI-driven solutions.
• Apply Edge AI for risk management and decision-making processes.
• Deploy and manage Edge AI solutions within financial environments.

This instructor-led, live training in Vietnam (online or onsite) is designed for intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for innovative healthcare solutions.

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

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

This instructor-led, live training in Vietnam (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.

By the conclusion 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, located in Vietnam (offered online or onsite), is designed for intermediate-level developers, system architects, and industry professionals seeking to leverage Edge AI to augment IoT applications with sophisticated data processing and analytical capabilities.

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

• Comprehend the core principles of Edge AI and its integration into IoT systems.
• Prepare and configure Edge AI environments suitable for IoT device operation.
• Create and install AI models on edge devices to support IoT applications.
• Deploy real-time data processing mechanisms and decision-making algorithms in IoT systems.
• Connect Edge AI solutions with various IoT protocols and platform ecosystems.
• Address ethical concerns and adopt best practices for Edge AI deployment 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 settings where speed, reliability, and offline operation are crucial.

Upon completion of this training, participants will be able 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 to achieve low-latency inference.
• Integrate edge intelligence with sensors, actuators, and industrial protocols.

Course Format

• Interactive lectures and discussions.
• Extensive 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 details.