Cambricon MLU Development with BANGPy and Neuware Training Course

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

Upon completion 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.

6G and the Intelligent Edge is a forward-looking course that explores the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to support intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT architects who wish to understand and design next-generation distributed architectures leveraging the synergy of 6G connectivity and intelligent edge systems.

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

• Understand how 6G will transform edge computing and IoT architectures.
• Design distributed systems for ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge for intelligent decision-making.
• Plan scalable, secure, and resilient 6G-ready edge infrastructures.
• Evaluate business and operational models enabled by 6G-edge convergence.

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation with 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 Romania (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 Romania (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 Romania (online or onsite) 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.

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

• Identifying security risks and vulnerabilities within Edge AI deployments.
• Applying encryption and authentication methods to protect data.
• Designing resilient Edge AI architectures capable of withstanding cyber threats.
• Utilizing secure strategies for deploying AI models in edge environments.

Huawei's Ascend CANN toolkit empowers developers to execute high-performance AI inference on edge devices like the Ascend 310. By providing essential tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources, CANN addresses the unique challenges of edge computing.

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 completing this course, participants will be able to:

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

Course Format

• Interactive lectures paired with live demonstrations.
• Practical lab exercises featuring edge-specific models and use cases.
• Live deployment examples on both virtual and physical edge hardware.

Customization Options

• For tailored training options, please reach out to us to arrange your personalized session.

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

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

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

• Evaluate the compatibility of existing 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 various platforms.
• Address practical challenges related to cross-architecture support and deployment.

Format of the Course

• Interactive lecture and discussion.
• Hands-on code translation and performance comparison labs.
• Guided exercises focused on multi-GPU adaptation strategies.

Course Customization Options

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

This instructor-led, live training in Romania (online or onsite) is designed for agritech professionals, IoT specialists, and AI engineers at the beginner to intermediate level who aim to develop and deploy Edge AI solutions for smart farming.

Upon completing this training, participants will be able to:

• Grasp the significance 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 Romania (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 Romania (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 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 Romania (online or onsite) is designed for intermediate to advanced computer vision engineers, AI developers, and IoT professionals who aim 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 for performance, power efficiency, and low-latency inference.

This instructor-led live training in Romania (online or on-site) targets intermediate-level finance professionals, fintech developers, and AI specialists who want to implement Edge AI solutions in the financial industry.

By the conclusion 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 Romania (online or onsite) targets intermediate-level healthcare professionals, biomedical engineers, and AI developers seeking 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 Romania (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.

Ascend, Biren, and Cambricon represent leading AI hardware platforms in China, each providing distinct acceleration and profiling tools tailored for large-scale AI workloads.

This instructor-led live training, available online or onsite, targets advanced AI infrastructure and performance engineers aiming to optimize model inference and training processes across these diverse Chinese AI chip ecosystems.

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

• Evaluate model performance on Ascend, Biren, and Cambricon platforms.
• Pinpoint system bottlenecks and inefficiencies in memory and compute resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Refine deployment pipelines to enhance throughput and reduce latency.

Course Format

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

Customization Options

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