Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level telecom professionals, AI engineers, and IoT specialists who wish to explore how 5G networks accelerate Edge AI applications.

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

• Understand the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimized for low-latency applications in 5G environments.
• Implement real-time decision-making systems using Edge AI and 5G connectivity.
• Optimize AI workloads for efficient performance on edge devices.

This forward-looking course examines the convergence of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, adaptive, and ultra-low-latency infrastructures.

Designed for intermediate-level IT architects, this instructor-led live training (available online or onsite) enables participants to understand and design next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be equipped to:

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

Course Format

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

Customization Options

• To request a customized training program for this course, please get in touch with us to arrange your session.

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.

This instructor-led, live training in the UAE (online or on-site) is designed for advanced-level cybersecurity professionals, AI engineers, and IoT developers who aim to implement robust security measures and resilience strategies for Edge AI systems.

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

• Understand the security risks and vulnerabilities associated with Edge AI deployments.
• Implement encryption and authentication techniques to protect data.
• Design resilient Edge AI architectures that can withstand cyber threats.
• Apply secure AI model deployment strategies in edge environments.

Huawei's Ascend CANN toolkit empowers powerful AI inference on edge devices like the Ascend 310. It provides the essential tools needed to compile, optimize, and deploy models in environments where computing power and memory are limited.

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

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

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Build lightweight inference pipelines using MindSpore Lite and AscendCL.
• Optimize model performance for environments with constrained compute and memory.
• Deploy and monitor AI applications in real-world edge scenarios.

Course Format

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

Customization Options

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

Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide alternatives to CUDA that are specifically designed for the local AI and high-performance computing (HPC) markets.

This instructor-led live training, available both online and onsite, is designed for advanced-level GPU programmers and infrastructure specialists who aim to migrate and optimize their existing CUDA applications for deployment on Chinese hardware platforms.

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

• Evaluating the compatibility of existing CUDA workloads with Chinese chip alternatives.
• Porting CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Comparing performance across platforms and identifying key optimization areas.
• Addressing practical challenges related to cross-architecture support and deployment.

Course Format

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

Course Customization Options

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

This instructor-led live training in the UAE (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.

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

• Grasp the role of Edge AI in precision agriculture.
• Deploy AI-driven systems for monitoring crops and livestock.
• Create automated irrigation and environmental sensing solutions.
• Enhance agricultural efficiency through real-time Edge AI analytics.

This instructor-led live training in the UAE (online or onsite) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who aim 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 designed for 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 designed for intermediate to advanced computer vision engineers, AI developers, and IoT professionals seeking to implement and optimize computer vision models for real-time processing on edge devices.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of Edge AI and its 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 to enhance performance, power efficiency, and reduce inference latency.

This instructor-led, live training in the UAE (available online or onsite) is designed for intermediate-level finance professionals, fintech developers, and AI specialists aiming 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 (the UAE / online or onsite) is tailored for intermediate-level AI developers, biomedical engineers, and healthcare professionals looking to leverage Edge AI for innovative medical solutions.

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

• Grasping the significance and advantages of Edge AI in the healthcare sector.
• Creating and deploying AI models on edge devices tailored for healthcare use.
• Applying Edge AI solutions within diagnostic tools and wearable devices.
• Designing and implementing patient monitoring systems utilizing Edge AI.
• Navigating ethical and regulatory requirements associated with healthcare AI applications.

This instructor-led live training in the UAE (available online or onsite) is designed for intermediate-level industrial engineers, manufacturing professionals, and AI developers who aim to implement Edge AI solutions in industrial automation.

Upon completing this training, participants will be able to:

• Grasp the role of Edge AI in industrial automation.
• Implement predictive maintenance solutions leveraging Edge AI.
• Utilize AI techniques for quality control within manufacturing processes.
• Optimize industrial processes using Edge AI.
• Deploy and manage Edge AI solutions in industrial settings.

Ascend, Biren, and Cambricon stand out as premier AI hardware solutions in China, each providing specialized acceleration and profiling capabilities tailored for large-scale AI operations.

This live, instructor-led training (available online or onsite) is designed for advanced AI infrastructure and performance engineers aiming to enhance model inference and training processes across these diverse Chinese AI chip ecosystems.

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

• Conduct benchmarking of models on Ascend, Biren, and Cambricon environments.
• Diagnose system bottlenecks and identify memory or compute inefficiencies.
• Implement optimizations at the graph, kernel, and operator levels.
• Refine deployment pipelines to maximize throughput and minimize latency.

Course Delivery Format

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

Customization Options

• For tailored training aligned with your specific performance environment or model architecture, please contact us to arrange a personalized session.