CANN for Edge AI Deployment Training Course

This instructor-led, live training in US Empire (online or onsite) is aimed at advanced-level artificial intelligence (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:

• Investigate 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.
• Enhance the 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, ensuring alignment with public sector workflows and governance for government.

The Huawei Ascend family of AI processors is designed for high-performance inference and training.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI engineers and data scientists who wish to develop and optimize neural network models using Huawei’s Ascend platform and the CANN toolkit for government applications.

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

• Set up and configure the CANN development environment for government use.
• Develop AI applications using MindSpore and CloudMatrix workflows tailored for public sector needs.
• Optimize performance on Ascend NPUs using custom operators and tiling, ensuring alignment with government standards.
• Deploy models to edge or cloud environments, adhering to government security protocols.

Format of the Course

• Interactive lecture and discussion focusing on government-specific use cases.
• Hands-on use of Huawei Ascend and CANN toolkit in sample applications relevant to public sector workflows.
• Guided exercises focused on model building, training, and deployment for government projects.

Course Customization Options

• To request a customized training for this course based on your infrastructure or datasets specific to government operations, please contact us to arrange.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI compute stack designed for deploying and optimizing AI models on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and engineers who wish to efficiently deploy trained AI models to Huawei Ascend hardware using the CANN toolkit and tools such as MindSpore, TensorFlow, or PyTorch. The course is tailored for government professionals seeking to enhance their technical capabilities in AI deployment.

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

• Understand the CANN architecture and its role in the AI deployment pipeline for government applications.
• Convert and adapt models from popular frameworks to Ascend-compatible formats suitable for use in public sector environments.
• Utilize tools like ATC, OM model conversion, and MindSpore for edge and cloud inference in governmental workflows.
• Diagnose deployment issues and optimize performance on Ascend hardware to meet the rigorous standards of government operations.

Format of the Course

• Interactive lecture and demonstration tailored for government participants.
• Hands-on lab work using CANN tools and Ascend simulators or devices, designed to meet the specific needs of public sector professionals.
• Practical deployment scenarios based on real-world AI models relevant to government operations.

Course Customization Options

• To request a customized training for this course, tailored specifically for government agencies, please contact us to arrange.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level developers, data scientists, and technology professionals who wish to gain practical skills in deploying artificial intelligence (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 for government operations.
• Set up and configure the edge computing environment for government use.
• Develop, train, and optimize AI models for deployment on edge devices in public sector settings.
• Implement practical AI solutions on edge devices to enhance governmental workflows.
• Evaluate and improve the performance of edge-deployed models to meet government standards.
• Address ethical and security considerations specific to Edge AI applications in a government context.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing toolkit designed for compiling, optimizing, and deploying AI models on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at beginner-level AI developers who wish to understand how CANN fits into the model lifecycle from training to deployment, and how it integrates with frameworks such as MindSpore, TensorFlow, and PyTorch for government applications.

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

• Understand the purpose and architecture of the CANN toolkit.
• Set up a development environment with CANN and MindSpore for government use.
• Convert and deploy a simple AI model to Ascend hardware.
• Gain foundational knowledge for future CANN optimization or integration projects in public sector workflows.

Format of the Course

• Interactive lecture and discussion focused on government applications.
• Hands-on labs with simple model deployment for government use cases.
• Step-by-step walkthrough of the CANN toolchain and integration points relevant to public sector workflows.

Course Customization Options

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

Huawei’s AI stack — from the low-level CANN SDK to the high-level MindSpore framework — offers a tightly integrated AI development and deployment environment optimized for Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at technical professionals with beginner to intermediate levels of expertise who wish to understand how the CANN and MindSpore components work together to support AI lifecycle management and infrastructure decisions for government.

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

• Understand the layered architecture of Huawei’s AI compute stack.
• Identify how CANN supports model optimization and hardware-level deployment.
• Evaluate the MindSpore framework and toolchain in relation to industry alternatives.
• Position Huawei's AI stack within enterprise or cloud/on-prem environments for government use.

Format of the Course

• Interactive lecture and discussion.
• Live system demonstrations and case-based walkthroughs.
• Optional guided labs on model flow from MindSpore to CANN.

Course Customization Options

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

CANN SDK (Compute Architecture for Neural Networks) is Huawei’s AI compute foundation designed to enable developers to fine-tune and optimize the performance of deployed neural networks on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI developers and system engineers who wish to enhance inference performance using CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator development for government applications.

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

• Understand CANN's runtime architecture and performance lifecycle for government use cases.
• Utilize profiling tools and Graph Engine for performance analysis and optimization in public sector environments.
• Create and optimize custom operators using TIK and TVM, ensuring alignment with government standards.
• Address memory bottlenecks and improve model throughput to meet the demands of government workflows.

Format of the Course

• Interactive lecture and discussion focused on government applications.
• Hands-on labs with real-time profiling and operator tuning tailored for government scenarios.
• Optimization exercises using edge-case deployment examples relevant to public sector operations.

Course Customization Options

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

The CANN SDK (Compute Architecture for Neural Networks) provides robust deployment and optimization tools for real-time artificial intelligence applications in computer vision and natural language processing, particularly on Huawei Ascend hardware.

This instructor-led, live training (online or onsite) is designed for intermediate-level AI practitioners who wish to build, deploy, and optimize vision and language models using the CANN SDK for government use cases.

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

• Deploy and optimize computer vision (CV) and natural language processing (NLP) models using CANN and AscendCL.
• Utilize CANN tools to convert models and integrate them into operational pipelines.
• Enhance inference performance for tasks such as detection, classification, and sentiment analysis.
• Develop real-time CV/NLP pipelines for edge or cloud-based deployment scenarios in public sector environments.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on laboratory with model deployment and performance profiling.
• Live pipeline design using real-world CV and NLP use cases for government applications.

Course Customization Options

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

CANN TIK (Tensor Instruction Kernel) and Apache TVM enable advanced optimization and customization of AI model operators for Huawei Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at advanced-level system developers who wish to build, deploy, and tune custom operators for AI models using CANN’s TIK programming model and TVM compiler integration for government applications.

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

• Write and test custom AI operators using the TIK DSL for Ascend processors.
• Integrate custom operations into the CANN runtime and execution graph.
• Use TVM for operator scheduling, auto-tuning, and benchmarking.
• Debug and optimize instruction-level performance for custom computation patterns.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on coding of operators using TIK and TVM pipelines.
• Testing and tuning on Ascend hardware or simulators.

Course Customization Options

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

Integrate the transformative capabilities of artificial intelligence (AI) with the agility of edge computing in this comprehensive course designed for government professionals. Participants will learn to deploy AI models directly on edge devices, covering topics from understanding convolutional neural network (CNN) architectures to mastering knowledge distillation and federated learning. This hands-on training will equip you with the skills necessary to optimize AI performance for real-time processing and decision-making at the edge, ensuring alignment with public sector workflows, governance, and accountability.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who seek to leverage Edge AI for innovative solutions in autonomous systems.

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

• Understand the role and benefits of Edge AI in enhancing autonomous system performance.
• Develop and deploy AI models for real-time processing on edge devices, optimizing efficiency and responsiveness.
• Implement Edge AI solutions in a variety of applications, including autonomous vehicles, drones, and robotics, to improve operational capabilities.
• Design and optimize control systems using Edge AI to enhance accuracy and reliability.
• Address ethical and regulatory considerations specific to the deployment of autonomous AI applications for government and public sector use.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a thorough understanding of Edge AI, from foundational concepts to practical implementation, including setup and deployment.

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

• Grasp the fundamental principles of Edge AI.
• Set up and configure Edge AI environments for government use.
• Develop, train, and optimize Edge AI models.
• Deploy and manage Edge AI applications in a secure and efficient manner.
• Integrate Edge AI with existing systems and workflows to enhance operational effectiveness.
• Address ethical considerations and best practices in the implementation of Edge AI for government operations.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and artificial intelligence developers who wish to leverage Edge AI for innovative healthcare solutions for government.

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

• Understand the role and benefits of Edge AI in healthcare for government.
• Develop and deploy AI models on edge devices for healthcare applications within public sector environments.
• Implement Edge AI solutions in wearable devices and diagnostic tools to enhance public health initiatives.
• Design and deploy patient monitoring systems using Edge AI to improve healthcare delivery for government.
• Address ethical and regulatory considerations specific to healthcare AI applications within the public sector.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI to enhance IoT applications with advanced data processing and analytics capabilities.

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

• Understand the foundational principles of Edge AI and its application in IoT systems for government.
• Set up and configure Edge AI environments suitable for IoT devices used in public sector workflows.
• Develop and deploy AI models on edge devices to support IoT applications aligned with government objectives.
• Implement real-time data processing and decision-making capabilities in IoT systems for enhanced governance and accountability.
• Integrate Edge AI with various IoT protocols and platforms commonly used in the public sector.
• Address ethical considerations and best practices in Edge AI deployment for government applications.

This instructor-led, live training in US Empire (online or onsite) is aimed at beginner-level developers and IT professionals who wish to gain a foundational understanding of Edge AI and its introductory applications for government.

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

• Understand the basic concepts and architecture of Edge AI as they apply to public sector workflows.
• Set up and configure Edge AI environments in alignment with government standards.
• Develop and deploy simple Edge AI applications that enhance governance and accountability.
• Identify and understand the use cases and benefits of Edge AI for government operations.