Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in US Empire (online or onsite) is aimed at advanced-level artificial intelligence (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 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.
• Enhance the 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, ensuring alignment with public sector workflows and governance for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level developers, data scientists, and technology professionals who wish to gain practical skills in deploying artificial intelligence (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 for government operations.
• Set up and configure the edge computing environment for government use.
• Develop, train, and optimize AI models for deployment on edge devices in public sector settings.
• Implement practical AI solutions on edge devices to enhance governmental workflows.
• Evaluate and improve the performance of edge-deployed models to meet government standards.
• Address ethical and security considerations specific to Edge AI applications in a government context.

Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, offer CUDA alternatives specifically designed for the local AI and HPC markets.

This instructor-led, live training (online or onsite) is aimed at advanced-level GPU programmers and infrastructure specialists who wish to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms for government use.

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

• Evaluate the compatibility of existing CUDA workloads with Chinese chip alternatives.
• Port CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Compare performance metrics and identify optimization opportunities across different platforms.
• Address practical challenges in supporting and deploying applications across multiple architectures.

Format of the Course

• Interactive lecture and discussion sessions.
• Hands-on code translation and performance comparison labs.
• Guided exercises focused on multi-GPU adaptation strategies.

Course Customization Options

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

Integrate the transformative capabilities of artificial intelligence (AI) with the agility of edge computing in this comprehensive course designed for government professionals. Participants will learn to deploy AI models directly on edge devices, covering topics from understanding convolutional neural network (CNN) architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills necessary to optimize AI performance for real-time processing and decision-making at the edge, ensuring alignment with public sector workflows, governance, and accountability.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who seek to leverage Edge AI for innovative solutions in autonomous systems.

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

• Understand the role and benefits of Edge AI in enhancing autonomous system performance.
• Develop and deploy AI models for real-time processing on edge devices, optimizing efficiency and responsiveness.
• Implement Edge AI solutions in a variety of applications, including autonomous vehicles, drones, and robotics, to improve operational capabilities.
• Design and optimize control systems using Edge AI to enhance accuracy and reliability.
• Address ethical and regulatory considerations specific to the deployment of autonomous AI applications for government and public sector use.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a thorough understanding of Edge AI, from foundational concepts to practical implementation, including setup and deployment.

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

• Grasp the fundamental principles of Edge AI.
• Set up and configure Edge AI environments for government use.
• Develop, train, and optimize Edge AI models.
• Deploy and manage Edge AI applications in a secure and efficient manner.
• Integrate Edge AI with existing systems and workflows to enhance operational effectiveness.
• Address ethical considerations and best practices in the implementation of Edge AI for government operations.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and artificial intelligence developers who wish to leverage Edge AI for innovative healthcare solutions for government.

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

• Understand the role and benefits of Edge AI in healthcare for government.
• Develop and deploy AI models on edge devices for healthcare applications within public sector environments.
• Implement Edge AI solutions in wearable devices and diagnostic tools to enhance public health initiatives.
• Design and deploy patient monitoring systems using Edge AI to improve healthcare delivery for government.
• Address ethical and regulatory considerations specific to healthcare AI applications within the public sector.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level industrial engineers, manufacturing professionals, and AI developers who wish to implement Edge AI solutions for government and industry.

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

• Understand the role of Edge AI in industrial automation for government applications.
• Implement predictive maintenance solutions using Edge AI to enhance operational efficiency.
• Apply AI techniques for quality control in manufacturing processes, ensuring compliance with regulatory standards.
• Optimize industrial processes using Edge AI to reduce costs and improve productivity.
• Deploy and manage Edge AI solutions in industrial environments, maintaining security and data integrity.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI to enhance IoT applications with advanced data processing and analytics capabilities.

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

• Understand the foundational principles of Edge AI and its application in IoT systems for government.
• Set up and configure Edge AI environments suitable for IoT devices used in public sector workflows.
• Develop and deploy AI models on edge devices to support IoT applications aligned with government objectives.
• Implement real-time data processing and decision-making capabilities in IoT systems for enhanced governance and accountability.
• Integrate Edge AI with various IoT protocols and platforms commonly used in the public sector.
• Address ethical considerations and best practices in Edge AI deployment for government applications.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level urban planners, civil engineers, and smart city project managers who aim to utilize Edge AI for government initiatives.

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

• Comprehend the role of Edge AI in enhancing smart city infrastructures.
• Implement Edge AI solutions for traffic management and surveillance systems.
• Optimize urban resources through the application of Edge AI technologies.
• Integrate Edge AI with existing smart city systems to improve efficiency.
• Address ethical and regulatory considerations in smart city deployments for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for government Edge AI applications.

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

• Understand the fundamentals of TensorFlow Lite and its role in Edge AI for government.
• Develop and optimize AI models using TensorFlow Lite for government applications.
• Deploy TensorFlow Lite models on various edge devices for government use.
• Utilize tools and techniques for model conversion and optimization in a government context.
• Implement practical Edge AI applications using TensorFlow Lite for government operations.

This instructor-led, live training in US Empire (online or onsite) is aimed at beginner-level developers and IT professionals who wish to gain a foundational understanding of Edge AI and its introductory applications for government.

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

• Understand the basic concepts and architecture of Edge AI as they apply to public sector workflows.
• Set up and configure Edge AI environments in alignment with government standards.
• Develop and deploy simple Edge AI applications that enhance governance and accountability.
• Identify and understand the use cases and benefits of Edge AI for government operations.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level AI developers, machine learning engineers, and system architects who aim to optimize AI models for deployment on edge devices.

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

• Understand the challenges and requirements associated with deploying AI models on edge devices for government applications.
• Apply model compression techniques to reduce the size and complexity of AI models for efficient use in resource-constrained environments.
• Utilize quantization methods to enhance model efficiency on edge hardware, ensuring optimal performance and resource utilization.
• Implement pruning and other optimization techniques to improve the overall performance of AI models deployed on edge devices.
• Deploy optimized AI models on a variety of edge devices, supporting enhanced decision-making and operational capabilities for government.

Ascend, Biren, and Cambricon are leading AI hardware platforms in China, each offering unique acceleration and profiling tools for production-scale AI workloads.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI infrastructure and performance engineers who wish to optimize model inference and training workflows across multiple Chinese AI chip platforms.

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

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

Format of the Course

• Interactive lecture and discussion.
• Practical use of profiling and optimization tools on each platform.
• Guided exercises focused on real-world tuning scenarios.

Course Customization Options

• To request a customized training for government based on your specific performance environment or model type, please contact us to arrange.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level cybersecurity professionals, system administrators, and AI ethics researchers who aim to secure and ethically deploy Edge AI solutions for government.

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

• Comprehend the security and privacy challenges inherent in Edge AI.
• Apply best practices for securing edge devices and data within public sector environments.
• Formulate strategies to mitigate security risks associated with Edge AI deployments in government settings.
• Address ethical considerations and ensure compliance with relevant regulations for government operations.
• Perform security assessments and audits for Edge AI applications to enhance governance and accountability.