Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training (online or onsite) is designed for government and 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 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.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers, data scientists, and technology enthusiasts who seek to acquire practical skills in deploying artificial intelligence (AI) models on edge devices for a variety of 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 deployment on edge devices. - Implement practical AI solutions on edge devices. - Evaluate and enhance the performance of models deployed at the edge. - Address ethical and security considerations in Edge AI applications. This training is tailored to align with public sector workflows, governance, and accountability, ensuring that participants are well-equipped to apply these skills effectively for government projects.

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

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

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

• Evaluate the compatibility of current 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 lectures and discussions.
• Hands-on code translation and performance comparison labs.
• Guided exercises focusing on multi-GPU adaptation strategies.

Course Customization Options for Government

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

This comprehensive course integrates the transformative power of artificial intelligence (AI) with the agility of edge computing. 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 is designed to equip professionals with the skills necessary to optimize AI performance for real-time processing and decision-making at the edge, ensuring alignment with public sector workflows and governance for government applications.

This instructor-led, live training (online or onsite) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who aim to harness Edge AI for innovative solutions in the field of autonomous systems. By the end of this training, participants will be able to: - Comprehend the role and advantages of Edge AI in autonomous systems. - Develop and deploy AI models for real-time processing on edge devices. - Implement Edge AI solutions for applications in autonomous vehicles, drones, and robotics. - Design and optimize control systems using Edge AI methodologies. - Address ethical and regulatory considerations relevant to autonomous AI applications, ensuring compliance with standards for government use.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI, from conceptual foundations 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 for government. - Address ethical considerations and best practices in Edge AI implementation.

This instructor-led, live training (available online or onsite) is designed for intermediate-level healthcare professionals, biomedical engineers, and artificial intelligence developers who aim to utilize 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, ensuring alignment with public sector workflows, governance, and accountability for government.

This instructor-led, live training (available online or on-site) is designed for intermediate-level industrial engineers, manufacturing professionals, and AI developers who aim to implement Edge AI solutions in the context of industrial automation. By the end of this training, participants will be able to: - Understand the role of Edge AI in enhancing industrial automation. - Implement predictive maintenance solutions utilizing Edge AI. - Apply AI techniques to ensure quality control in manufacturing processes. - Optimize industrial processes through the use of Edge AI. - Deploy and manage Edge AI solutions effectively in industrial settings. This training is tailored to align with public sector workflows, governance, and accountability, ensuring that participants are equipped with the skills necessary for government applications.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who aim 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:

• Comprehend the core principles of Edge AI and its application in IoT systems.
• Establish and configure Edge AI environments for IoT devices.
• Create and deploy AI models on edge devices to support IoT applications.
• Execute real-time data processing and decision-making within IoT frameworks.
• Integrate Edge AI with a variety of IoT protocols and platforms.
• Address ethical considerations and best practices in the deployment of Edge AI for government and industry use cases.

This instructor-led, live training (online or onsite) is designed for intermediate-level urban planners, civil engineers, and smart city project managers who seek to leverage Edge AI for government initiatives. By the end of this training, participants will be able to: - Comprehend the role of Edge AI in smart city infrastructures. - Implement Edge AI solutions for traffic management and surveillance. - Optimize urban resources using Edge AI technologies. - Integrate Edge AI with existing smart city systems. - Address ethical and regulatory considerations in smart city deployments for government.

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

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 deployment in government settings.
• Deploy TensorFlow Lite models on various edge devices used in public sector applications.
• Utilize tools and techniques for model conversion and optimization suitable for government workflows.
• Implement practical Edge AI applications using TensorFlow Lite to enhance public sector operations.

This instructor-led, live training in [location] (online or onsite) is designed for government beginner-level developers and IT professionals who wish to gain a foundational understanding of Edge AI and its initial applications. By the end of this training, participants will be able to: - Comprehend the fundamental concepts and architecture of Edge AI. - Set up and configure Edge AI environments for government use. - Develop and deploy basic Edge AI applications. - Recognize and understand the use cases and benefits of Edge AI in public sector workflows.

This instructor-led, live training in [location] (online or onsite) is aimed at intermediate-level AI developers, machine learning engineers, and system architects who wish to optimize AI models for edge deployment for government applications. By the end of this training, participants will be able to: - Understand the challenges and requirements of deploying AI models on edge devices. - Apply model compression techniques to reduce the size and complexity of AI models. - Utilize quantization methods to enhance model efficiency on edge hardware. - Implement pruning and other optimization techniques to improve model performance. - Deploy optimized AI models on various edge devices for government use.

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

This instructor-led, live training (available online or onsite) is designed for advanced-level AI infrastructure and performance engineers who seek 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 inefficiencies in memory and compute performance.
• Implement graph-level, kernel-level, and operator-level optimizations.
• Refine deployment pipelines to enhance throughput and reduce latency.

Format of the Course

• Interactive lecture and discussion sessions.
• Hands-on use of profiling and optimization tools for each platform.
• Guided exercises focusing on practical tuning scenarios.

Course Customization Options

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

This instructor-led, live training (conducted 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:

• Understand the security and privacy challenges associated with Edge AI.
• Implement best practices for securing edge devices and data.
• Develop strategies to mitigate security risks in Edge AI deployments.
• Address ethical considerations and ensure compliance with relevant regulations.
• Conduct thorough security assessments and audits for Edge AI applications.