Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in Norway (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists keen on understanding how 5G networks accelerate Edge AI applications.

Upon completion 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 is an innovative course that investigates the convergence of 6G wireless technologies, edge computing, IoT ecosystems, and AI-powered data processing to build intelligent, adaptive, and low-latency infrastructures.

This instructor-led live training (available online or onsite) targets intermediate-level IT architects looking to master and design next-generation distributed architectures that leverage the combined strengths of 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Grasp how 6G will revolutionize edge computing and IoT architectures.
• Develop distributed systems for autonomous operations, high bandwidth, and ultra-low latency.
• Implement AI and data analytics at the edge to enable intelligent decision-making.
• Architect scalable, secure, and resilient edge infrastructures prepared for 6G.
• Assess the business and operational models facilitated by the convergence of 6G and edge computing.

Course Format

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation using optional edge or container tools.

Course Customization Options

• For customized training arrangements, please contact us.

This instructor-led, live training in Norway (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 live, instructor-led training in Norway (online or onsite) is designed for intermediate developers, data scientists, and technology enthusiasts looking to gain practical skills in deploying AI models on edge devices for various applications.

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

• Grasp the core principles of Edge AI and its advantages.
• Establish and configure the necessary edge computing infrastructure.
• Create, train, and refine AI models tailored for edge deployment.
• Deploy practical AI solutions onto edge hardware.
• Assess and enhance the performance of models running on the edge.
• Navigate ethical and security aspects inherent to Edge AI applications.

This instructor-led, live training in Norway (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 capable of:

• Identifying security risks and vulnerabilities associated with Edge AI deployments.
• Applying encryption and authentication techniques to protect data.
• Architecting resilient Edge AI systems capable of withstanding cyber threats.
• Executing secure AI model deployment strategies within edge environments.

Huawei's Ascend CANN toolkit facilitates high-performance AI inference on edge devices, such as the Ascend 310. It provides critical tools for compiling, optimizing, and deploying models in environments with limited compute power and memory.

This instructor-led live training, available online or onsite, is designed for intermediate-level AI developers and integrators looking to deploy and optimize models on Ascend edge devices using the CANN toolchain.

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

• Preparing and converting AI models for the Ascend 310 using CANN tools.
• Constructing lightweight inference pipelines with MindSpore Lite and AscendCL.
• Enhancing model performance in resource-constrained settings.
• Deploying and monitoring AI applications in real-world edge scenarios.

Course Format

• Interactive lectures and demonstrations.
• Practical lab exercises featuring edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Customization Options

• To arrange customized training for this course, please contact us.

Domestic GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide CUDA-compatible alternatives specifically designed for the local AI and HPC sectors.

This instructor-led live training, available online or onsite, is intended for advanced GPU developers and infrastructure experts seeking to migrate and optimize their existing CUDA applications for deployment on Chinese hardware.

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on code translation and performance benchmarking.
• Guided exercises targeting multi-GPU adaptation strategies.

Customization Options

• For tailored training aligned with your specific platform or CUDA project, please contact us to arrange a session.

This instructor-led, live training in Norway (online or onsite) is designed for beginner to intermediate 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 Norway (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 Norway (available online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI, covering everything from conceptual foundations to practical implementation, setup, and deployment.

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

• Grasp 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 solutions with existing systems and workflows.
• Address ethical considerations and adhere to best practices in Edge AI implementation.

This instructor-led, live training in Norway (online or onsite) targets intermediate to advanced computer vision engineers, AI developers, and IoT professionals who wish 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 fundamentals of Edge AI and its practical 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 enhanced performance, power efficiency, and low-latency inference.

This instructor-led, live training in Norway (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 Norway (online or onsite) targets 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 live, instructor-led training in Norway (available online or onsite) targets intermediate-level industrial engineers, manufacturing professionals, and AI developers who aim 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 represent the forefront of AI hardware platforms in China, each providing distinct acceleration and profiling capabilities tailored for large-scale AI workloads.

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

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

• Conduct benchmarks for models across Ascend, Biren, and Cambricon platforms.
• Pinpoint system bottlenecks and inefficiencies related to memory and compute resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Refine deployment pipelines to enhance both throughput and latency.

Course Format

• Engaging interactive lectures and discussions.
• Practical application of profiling and optimization tools on each respective platform.
• Guided exercises centered on real-world tuning scenarios.

Course Customization Options

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