Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in the UAE (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 the UAE (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.

Chinese GPU architectures like Huawei Ascend, Biren, and Cambricon MLUs provide alternatives to CUDA that are specifically designed for the local AI and HPC markets in the UAE.

This instructor-led training (online or at your location) is targeted at advanced GPU programmers and infrastructure specialists who want to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.

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

• Determine the compatibility of current CUDA workloads with Chinese chip alternatives.
• Migrate CUDA codebases to environments such as Huawei CANN, Biren SDK, and Cambricon BANGPy.
• Analyze performance differences and pinpoint optimization opportunities across various platforms.
• Overcome practical challenges in cross-architecture support and deployment.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for code translation and performance comparison.
• Guided exercises focusing on multi-GPU adaptation strategies.

Customization Options

• To request a customized training based on your platform or CUDA project, please contact us to arrange the details.

This instructor-led, live training in the UAE (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 the UAE (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 the UAE (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 the UAE (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 the UAE (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 the UAE (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.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level urban planners, civil engineers, and smart city project managers who wish to leverage Edge AI for smart city initiatives.

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

• Understand 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.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for 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.
• Develop and optimize AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on various edge devices.
• Utilize tools and techniques for model conversion and optimization.
• Implement practical Edge AI applications using TensorFlow Lite.

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level developers and IT professionals who wish to understand the fundamentals of Edge AI and its introductory applications.

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

• Understand the basic concepts and architecture of Edge AI.
• Set up and configure Edge AI environments.
• Develop and deploy simple Edge AI applications.
• Identify and understand the use cases and benefits of Edge AI.

This instructor-led, live training in the UAE (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.

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.

The leading AI hardware platforms in China—Ascend, Biren, and Cambricon—provide distinctive acceleration and profiling tools tailored for large-scale AI workloads.

This instructor-led training session (conducted either online or on-site) is designed for advanced-level engineers specializing in AI infrastructure and performance. The goal is to enhance their ability to optimize model inference and training processes across various Chinese AI chip platforms.

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

• Evaluate models using the Ascend, Biren, and Cambricon platforms.
• Detect system limitations and inefficiencies in memory and compute resources.
• Implement optimizations at the graph level, kernel level, and operator level.
• Refine deployment pipelines to boost throughput and reduce latency.

Course Format

• An interactive lecture combined with discussions.
• Practical use of profiling and optimization tools on each platform.
• Guided exercises centered around real-world tuning scenarios.

Customization Options for the Course

• If you require a customized training session based on your specific performance environment or model type, please contact us to arrange this.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level cybersecurity professionals, system administrators, and AI ethics researchers who wish to secure and ethically deploy Edge AI solutions.

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

• Understand the security and privacy challenges in 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 regulations.
• Conduct security assessments and audits for Edge AI applications.