Edge AI with TensorFlow Lite Training Course

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

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

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

6G and the Intelligent Edge is an advanced course that delves into the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing. This course focuses on creating intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level IT architects who want to gain a deep understanding of how to design next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be able to:

• Understand how 6G technology will revolutionize edge computing and IoT architectures.
• Design distributed systems that support 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 new business and operational models made possible by the convergence of 6G and edge computing.

Format of the Course

• Interactive lectures and discussions.
• Case studies and practical architecture design exercises.
• Hands-on simulations 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 Taiwan (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 instructor-led, live training in Taiwan (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 Taiwan (online or onsite) is aimed at advanced-level cybersecurity professionals, AI engineers, and IoT developers who wish to implement robust security measures and resilience strategies for Edge AI systems.

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

• Understand security risks and vulnerabilities in Edge AI deployments.
• Implement encryption and authentication techniques for data protection.
• Design resilient Edge AI architectures that can withstand cyber threats.
• Apply secure AI model deployment strategies in edge environments.

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

This instructor-led, live training (available online or on-site) is tailored for intermediate-level developers who wish to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

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

• Set up and configure the development environments for BANGPy and Neuware.
• Create and optimize Python- and C++-based models for use with Cambricon MLUs.
• Deploy these models to edge and data center devices that run the Neuware runtime.
• Integrate machine learning workflows with specific acceleration features provided by MLUs.

Format of the Course

• Interactive lectures and discussions.
• Practical, hands-on use of BANGPy and Neuware for development and deployment tasks.
• Guided exercises focusing on optimization, integration, and testing processes.

Course Customization Options

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

Huawei's Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. This toolkit offers essential utilities for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

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

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

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

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on lab sessions with models and scenarios specific to edge devices.
• Real deployment examples on virtual or physical edge hardware.

Course Customization Options

• For a customized training session tailored to your needs, please contact us to arrange.

This instructor-led, live training in Taiwan (online or onsite) is aimed at beginner-level 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 Taiwan (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 Taiwan (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 Taiwan (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 Taiwan (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 Taiwan (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 Taiwan (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 Taiwan (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.