Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led live training in Bulgaria (online or onsite) targets intermediate-level telecom professionals, AI engineers, and IoT specialists interested in exploring the role of 5G networks in accelerating 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.

The '6G and the Intelligent Edge' course offers a forward-looking perspective on integrating 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to enable intelligent, adaptive, and low-latency infrastructures.

This instructor-led training, available online or onsite, targets intermediate-level IT architects seeking to grasp and design next-generation distributed architectures that leverage the synergy between 6G connectivity and intelligent edge systems.

Upon completing this course, participants will be able to:

• Comprehend 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 to facilitate intelligent decision-making.
• Plan scalable, secure, and resilient 6G-ready edge infrastructures.
• Evaluate business and operational models enabled by the convergence of 6G and edge technologies.

Course Format

• 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 Bulgaria (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 conducted in Bulgaria (online or onsite) is tailored for intermediate-level developers, data scientists, and tech enthusiasts aiming to acquire practical skills in deploying AI models on edge devices for diverse applications.

By the conclusion 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 Bulgaria (online or onsite) targets advanced cybersecurity professionals, AI engineers, and IoT developers who wish to implement robust security measures and resilience strategies for Edge AI systems.

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

• Grasp the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to protect data.
• Design resilient Edge AI architectures capable of withstanding cyber threats.
• Utilize secure strategies for deploying AI models in edge environments.

Huawei's Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. This suite offers vital tools for compiling, optimizing, and deploying models in environments where computational power and memory are limited.

This instructor-led, live training (available online or onsite) targets intermediate-level AI developers and integrators seeking 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 within constrained compute and memory settings.
• Deploying and monitoring AI applications in real-world edge scenarios.

Course Format

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

Course Customization Options

• For customized training options, please contact us to arrange.

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 session (available online or onsite) targets advanced-level GPU programmers and infrastructure specialists seeking to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.

Upon completion of this training, participants will be equipped 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 different platforms.
• Address practical challenges related to cross-architecture support and deployment.

Course Format

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

Customization Options

• To request a customized training session tailored to your specific platform or CUDA project, please contact us to arrange it.

This instructor-led, live training in Bulgaria (online or onsite) targets beginner to intermediate-level 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 Bulgaria (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 Bulgaria (online or onsite) is designed for intermediate-level developers and IT professionals who want to gain a comprehensive understanding of Edge AI, covering everything from conceptual foundations to practical implementation, including 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 with existing systems and workflows.
• Address ethical considerations and best practices in Edge AI implementation.

This instructor-led, live training in Bulgaria (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 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 Bulgaria (online or onsite) is tailored for intermediate-level finance professionals, fintech developers, and AI specialists who wish to implement Edge AI solutions in financial services.

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

• Grasp the significance of Edge AI in financial services.
• Build fraud detection systems using Edge AI.
• Improve customer service through AI-powered solutions.
• Utilize Edge AI for risk management and strategic decision-making.
• Deploy and oversee Edge AI solutions in financial settings.

This instructor-led, live training in Bulgaria (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 Bulgaria (online or onsite) is tailored for 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 stand as premier AI hardware platforms in China, providing distinct acceleration and profiling solutions tailored for large-scale AI workloads in production.

This instructor-led live training (available online or onsite) targets advanced AI infrastructure and performance engineers who aim to optimize model inference and training processes across various Chinese AI chip ecosystems.

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

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

Course Format

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

Customization Options

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