Cambricon MLU Development with BANGPy and Neuware Training Course

This instructor-led, live training in India (online or onsite) is designed for 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.

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

This instructor-led live training, available both online and onsite, is tailored for intermediate-level IT architects aiming to grasp and design next-generation distributed architectures that harness the synergy between 6G connectivity and intelligent edge systems.

After completing this course, participants will be equipped to:

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

Course Format

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

Customization Options

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

This instructor-led live training in India (online or on-site) is designed for advanced-level AI practitioners, researchers, and developers who aim to master the latest Edge AI advancements, optimize their models for edge deployment, and explore specialized applications across various sectors.

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

• Investigate advanced methods for developing and optimizing Edge AI models.
• Apply cutting-edge strategies for deploying AI models on edge devices.
• Leverage specialized tools and frameworks for complex Edge AI applications.
• Enhance the performance and efficiency of Edge AI solutions.
• Explore innovative use cases and emerging trends in the Edge AI landscape.
• Tackle advanced ethical and security challenges associated with Edge AI deployments.

This instructor-led live training in India (online or onsite) targets intermediate-level developers, data scientists, and tech enthusiasts seeking practical skills in deploying AI models on edge devices for diverse applications.

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

• Comprehend the core principles of Edge AI and its advantages.
• Establish and configure the edge computing environment.
• Develop, train, and optimize AI models specifically for edge deployment.
• Deploy practical AI solutions on edge devices.
• Assess and enhance the performance of models deployed on the edge.
• Tackle ethical and security issues inherent in Edge AI applications.

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

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

• Grasp 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.
• Deploy secure AI models within edge environments.

The Huawei Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. It offers critical tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

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 training, participants will be equipped to:

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

Format of the Course

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

Course Customization Options

• To request a customized training for this course, 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 High-Performance Computing (HPC) markets.

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

Upon completion 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 key optimization points across different platforms.
• Address practical challenges related to cross-architecture support and deployment.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in India (online or onsite) is designed for 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 India (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 India (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 the initial concept to practical implementation, including setup and deployment.

Upon completing 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 adhere to best practices in Edge AI implementation.

This instructor-led, live training in India (online or onsite) is aimed at 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.

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

• Understand 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.
• Use frameworks like 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 India (online or onsite) targets intermediate-level finance professionals, fintech developers, and AI specialists who aim to implement Edge AI solutions in financial services.

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 live, instructor-led training in India (online or onsite) targets intermediate-level healthcare professionals, biomedical engineers, and AI developers who want to leverage Edge AI for innovative healthcare solutions.

Upon completing this training, participants will be able to:

• Grasp the role and advantages of Edge AI in the healthcare sector.
• Build and deploy AI models on edge devices for healthcare use cases.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems leveraging Edge AI.
• Navigate ethical and regulatory considerations in healthcare AI applications.

This instructor-led, live training in India (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 the forefront of AI hardware platforms in China, each providing distinct acceleration and profiling capabilities designed for large-scale AI workloads.

This instructor-led live training session (available online or onsite) is tailored for advanced-level AI infrastructure and performance engineers looking to enhance model inference and training workflows across various Chinese AI chip architectures.

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

• Evaluate and benchmark models across Ascend, Biren, and Cambricon environments.
• Pinpoint system bottlenecks and identify inefficiencies in memory and compute resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Optimize deployment pipelines to achieve superior throughput and reduced latency.

Training Format

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

Customization Options

• For tailored training sessions based on your specific performance environment or model requirements, please reach out to us to coordinate.