Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in Taiwan (online or onsite) targets intermediate-level telecom professionals, AI engineers, and IoT specialists interested in exploring how 5G networks accelerate Edge AI applications.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of 5G technology and its influence 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 Taiwan (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 completion of this training, participants will be able to:

• Investigate advanced techniques in Edge AI model development and optimization.
• Execute state-of-the-art 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.
• Address advanced ethical and security considerations in Edge AI deployments.

This instructor-led, live training in Taiwan (available online or onsite) is tailored for intermediate-level developers, data scientists, and tech enthusiasts seeking 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 designed for 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.

Huawei's Ascend CANN toolkit empowers AI inference on edge devices, such as the Ascend 310. This toolkit offers crucial tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

This instructor-led, live training (available online or 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.

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 for scenarios with constrained 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.

Course Customization Options

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

Domestic GPU solutions, including Huawei Ascend, Biren, and Cambricon MLUs, provide tailored alternatives to CUDA for the local AI and high-performance computing (HPC) sectors.

This live training session, facilitated by an expert instructor and available either online or on-site, targets advanced GPU developers and infrastructure specialists looking to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.

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

• Assessing the compatibility of current CUDA workloads with domestic chip alternatives.
• Porting CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Evaluating performance metrics and identifying optimization opportunities across different platforms.
• Resolving practical challenges related to cross-architecture support and deployment.

Course Format

• Interactive lectures and discussions.
• Practical labs involving code translation and performance benchmarking.
• Guided exercises focusing on multi-GPU adaptation strategies.

Customization Options

• To request a customized version of this training based on your specific platform or CUDA project, please contact us to arrange it.

This instructor-led, live training in Taiwan (online or onsite) is designed for 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 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 designed for intermediate-level developers and IT professionals who aim to gain a thorough understanding of Edge AI, spanning from conceptual foundations to practical implementation, including setup and deployment.

Upon completing this training, participants will be equipped to:

• Grasp the core concepts of Edge AI.
• Configure and set up Edge AI environments.
• Develop, train, and optimize Edge AI models.
• Deploy and manage Edge AI applications.
• Integrate Edge AI solutions with existing systems and workflows.
• Navigate ethical considerations and adhere to best practices in Edge AI implementation.

This instructor-led, live training in Taiwan (online or onsite) is designed for computer vision engineers, AI developers, and IoT professionals at the intermediate to advanced level 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 Taiwan (online or onsite) is designed for 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 capable of:

• Comprehending the role of Edge AI in financial services.
• Developing fraud detection systems utilizing Edge AI.
• Improving customer service through AI-driven solutions.
• Applying Edge AI for risk management and decision-making processes.
• Deploying and managing Edge AI solutions within 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.

Ascend, Biren, and Cambricon are prominent AI hardware platforms in China, each providing distinct acceleration and profiling tools for production-scale AI workloads.

This instructor-led live training (available online or onsite) targets advanced-level AI infrastructure and performance engineers seeking to optimize model inference and training workflows across multiple Chinese AI chip platforms.

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

• Benchmark models on Ascend, Biren, and Cambricon platforms.
• Identify system bottlenecks and memory/compute inefficiencies.
• Apply graph-level, kernel-level, and operator-level optimizations.
• Tune deployment pipelines to enhance throughput and reduce latency.

Course Format

• Interactive lectures and discussions.
• Hands-on practice with profiling and optimization tools on each platform.
• Guided exercises focused on practical tuning scenarios.

Course Customization Options

• To request a customized training session tailored to your specific performance environment or model type, please contact us to arrange.