Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in Italy (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists eager to explore how 5G networks enhance Edge AI applications.

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

• Grasp the fundamentals of 5G technology and its influence on Edge AI.
• Deploy AI models tailored for low-latency applications within 5G environments.
• Implement real-time decision-making systems leveraging Edge AI and 5G connectivity.
• Optimize AI workloads to ensure efficient performance on edge devices.

6G and the Intelligent Edge offers a forward-looking exploration into how 6G wireless technologies integrate with edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available online or onsite) is designed for intermediate-level IT architects looking to understand and design next-generation distributed architectures by leveraging the synergy between 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Grasp how 6G will transform edge computing and IoT architectures.
• Design distributed systems capable of 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 the business and operational models enabled by the convergence of 6G and edge technologies.

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation using 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 Italy (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 Italy (online or onsite) is designed for intermediate developers, data scientists, and technology enthusiasts who want to gain practical skills in deploying AI models on edge devices for diverse applications.

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

• Grasp the core principles of Edge AI and its advantages.
• Configure and set up the edge computing environment.
• Develop, train, and optimize AI models specifically for edge deployment.
• Implement functional AI solutions on edge devices.
• Assess and enhance the performance of models deployed at the edge.
• Tackle ethical and security aspects related to Edge AI applications.

This instructor-led, live training in Italy (online or onsite) is designed for advanced cybersecurity professionals, AI engineers, and IoT developers seeking to implement robust security measures and resilience strategies for Edge AI systems.

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

• Comprehend the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to protect data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Execute secure AI model deployment strategies within edge environments.

Huawei's Ascend CANN toolkit empowers developers to execute high-performance AI inference on edge hardware, including the Ascend 310. This toolkit offers critical capabilities for compiling, optimizing, and deploying models in environments where computational power and memory are limited.

This instructor-led live training, available either online or on-site, is designed for intermediate AI developers and integrators seeking to deploy and optimize models on Ascend edge devices using the CANN ecosystem.

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

• Prepare and convert AI models for the Ascend 310 using CANN utilities.
• Construct efficient inference pipelines utilizing MindSpore Lite and AscendCL.
• Enhance model performance tailored for constrained compute and memory resources.
• Deploy and oversee AI applications in practical edge scenarios.

Course Format

• Engaging lectures combined with live demonstrations.
• Practical laboratory sessions focusing on edge-specific models and use cases.
• Real-world deployment examples executed on virtual or physical edge hardware.

Customization Options

• To request a tailored training session for this course, please reach out to us for arrangements.

Domestic GPU architectures in China, including Huawei Ascend, Biren, and Cambricon MLUs, provide CUDA alternatives specifically designed for the local AI and High-Performance Computing (HPC) sectors.

This guided, live training session (available online or on-site) is designed for advanced GPU developers and infrastructure experts looking to migrate and optimize their existing CUDA applications for Chinese hardware platforms.

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

• Assess the compatibility of current CUDA workloads with Chinese chip alternatives.
• Transfer CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Evaluate performance metrics and identify optimization opportunities across different platforms.
• Resolve practical challenges related to cross-architecture support and deployment.

Course Format

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

Customization Options

• For tailored training based on your specific platform or CUDA project, please contact us to arrange a customized session.

Combine the transformative power of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, from understanding CNN architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills to optimize AI performance for real-time processing and decision-making at the edge.

This instructor-led, live training in Italy (online or onsite) is designed for beginner to intermediate-level agritech professionals, IoT specialists, and AI engineers looking 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 Italy (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 Italy (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI, covering the journey 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 Italy (online or onsite) is designed for intermediate to advanced computer vision engineers, AI developers, and IoT professionals looking to implement and optimize computer vision models for real-time processing on edge devices.

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

• Grasp the core principles of Edge AI and its role 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.
• Enhance AI models for superior performance, power efficiency, and low-latency inference.

This instructor-led live training, delivered Italy (either online or onsite), is designed for intermediate-level finance professionals, fintech developers, and AI specialists interested in implementing Edge AI solutions in the financial sector.

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 Italy (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.

Ascend, Biren, and Cambricon stand out as premier AI hardware platforms in China, each providing distinct acceleration and profiling capabilities tailored for large-scale AI production workloads.

This instructor-led live training, available online or onsite, targets advanced AI infrastructure and performance engineers seeking to optimize model inference and training processes across various Chinese AI chip architectures.

Upon completing this training, participants will be equipped to:

• Conduct benchmarks on Ascend, Biren, and Cambricon platforms.
• Diagnose system bottlenecks and identify inefficiencies in memory and compute resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Optimize deployment pipelines to enhance both throughput and reduce latency.

Course Format

• Interactive lectures and group discussions.
• Practical application of profiling and optimization tools specific to each platform.
• Guided exercises centered on real-world tuning scenarios.

Customization Options

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