CANN for Edge AI Deployment Training Course

This instructor-led live training session, conducted in US (either online or onsite), targets intermediate-level telecommunications professionals, AI engineers, and IoT specialists seeking to examine how 5G networks drive the acceleration of Edge AI applications for government use.

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

• Articulate the foundational principles of 5G technology and its specific impacts on Edge AI performance.
• Execute the deployment of AI models specifically optimized for low-latency operations within 5G environments.
• Establish real-time decision-making systems utilizing Edge AI and 5G connectivity standards.
• Refine AI workloads to achieve optimal efficiency on edge computing devices.

This 21-hour training in US guides IT architects in designing next-generation distributed systems. Explore 6G, edge computing, and AI integration for low-latency, scalable infrastructures for government. Gain practical skills for secure, resilient, and intelligent edge architectures to meet future public sector demands.

This instructor-led, live training in US (online or onsite) is intended for advanced-level AI practitioners, researchers, and developers aiming to master the latest advancements in Edge AI, optimize their AI models for edge deployment, and explore specialized applications across various industries, with a focus on relevance for government operations.

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

• Apply advanced techniques in Edge AI model development and optimization.
• Execute state-of-the-art strategies for deploying AI models on edge devices.
• Leverage specialized tools and frameworks for advanced Edge AI applications.
• Enhance the performance and efficiency of Edge AI solutions.
• Investigate innovative use cases and emerging trends in Edge AI.
• Address advanced ethical and security considerations in Edge AI deployments for government.

The Huawei Ascend series comprises AI processors engineered for high-performance inference and training operations.

This instructor-led, live training session, available online or in-person, is designed for intermediate-level AI engineers and data scientists seeking to develop and optimize neural network models utilizing Huawei’s Ascend platform and the CANN toolkit. This curriculum is tailored for government agencies requiring advanced AI infrastructure expertise.

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

• Establish and configure the CANN development environment.
• Develop AI applications through MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs by implementing custom operators and tiling techniques.
• Deploy models to edge or cloud environments for government use cases.

Course Format

• Interactive lectures and facilitated discussions.
• Hands-on application of Huawei Ascend and the CANN toolkit within sample applications.
• Guided exercises emphasizing model construction, training, and deployment.

Course Customization Options

• To request a customized training program aligned with specific infrastructure or dataset requirements, please contact us to arrange a consultation for government stakeholders.

This instructor-led, live training in US (online or onsite) is designed for intermediate-level developers, data scientists, and technical professionals seeking to acquire practical competencies in deploying AI models on edge devices for diverse public sector applications.

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

• Comprehend the foundational principles of Edge AI and its operational benefits.
• Configure and administer secure edge computing environments.
• Develop, train, and optimize AI models specifically for edge deployment.
• Implement functional AI solutions on designated edge devices.
• Assess and enhance the performance of models deployed on the edge.
• Navigate ethical frameworks and security protocols inherent to Edge AI applications.

This instructor-led, live training in US (delivered online or onsite) is targeted at advanced cybersecurity professionals, AI engineers, and IoT developers focused on implementing rigorous security measures and resilience strategies for Edge AI systems.

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

• Assess security risks and vulnerabilities in Edge AI deployments.
• Implement encryption and authentication techniques to ensure data protection.
• Design resilient Edge AI architectures capable of resisting cyber threats.
• Apply secure AI model deployment strategies in edge environments.

Cambricon Machine Learning Units (MLUs) represent specialized artificial intelligence hardware engineered for optimized inference and training workloads in both edge and data center environments.

This instructor-led, live training program, available in online or on-site formats, is designed for intermediate-level developers seeking to build and deploy artificial intelligence models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

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

• Establish and configure BANGPy and Neuware development environments.
• Develop and optimize Python- and C++-based models for Cambricon MLUs.
• Deploy models to edge and data center devices utilizing the Neuware runtime.
• Integrate machine learning workflows with MLU-specific acceleration features.

Instructional Methodology

• Interactive lectures and facilitated discussions.
• Hands-on application of BANGPy and Neuware for development and deployment tasks.
• Structured exercises emphasizing optimization, integration, and system testing.

Customization Opportunities for Government and Enterprise Entities

• Organizations seeking a customized training curriculum tailored to specific Cambricon device models or operational use cases are encouraged to contact us for coordination.

CANN (Compute Architecture for Neural Networks) constitutes Huawei’s artificial intelligence computing toolkit, designed to compile, optimize, and deploy AI models on Ascend AI processors for government and public sector applications.

This instructor-led, live training session (available online or onsite) is designed for entry-level AI developers seeking to comprehend the integration of CANN within the model lifecycle, from training through to deployment, and its interoperability with frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completion of this training, participants will possess the capability to:

• Comprehend the objectives and architectural design of the CANN toolkit.
• Establish a development environment incorporating CANN and MindSpore.
• Convert and deploy basic AI models onto Ascend hardware.
• Acquire foundational knowledge supporting future CANN optimization and integration projects.

Instructional Methodology

• Interactive lectures and facilitated discussions.
• Practical laboratory exercises involving simple model deployment.
• Detailed walkthrough of the CANN toolchain and integration points.

Customization Options for the Course

• To request a tailored training program for this course, please contact the designated office to arrange suitable provisions.

Huawei's AI infrastructure, ranging from the foundational CANN SDK to the advanced MindSpore framework, provides a cohesive environment for AI development and deployment, specifically optimized for Ascend hardware performance.

This instructor-led training session, available in online or on-site formats, is designed for technical professionals at the beginner to intermediate level who seek to understand the interoperability of CANN and MindSpore components in supporting AI lifecycle management and infrastructure decision-making for government and other sectors.

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

• Comprehend the hierarchical architecture of Huawei's AI computing stack.
• Recognize the role of CANN in enabling model optimization and hardware-level execution.
• Assess the MindSpore framework and associated toolchain in comparison to industry-standard alternatives.
• Evaluate the placement of Huawei's AI stack within enterprise or hybrid cloud/on-premises environments.

Instructional Format

• Interactive lectures and facilitated discussions.

Customization Options for the Course

• To initiate a customized training program tailored for government or specific organizational needs, please establish contact for scheduling arrangements.

The CANN SDK (Compute Architecture for Neural Networks) serves as Huawei’s foundational AI computing platform, enabling developers to calibrate and enhance the operational efficiency of neural networks deployed on Ascend AI processors.

This instructor-led, live instruction (available online or on-site) is designed for senior AI developers and systems engineers seeking to refine inference capabilities through CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator creation.

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

• Comprehend the CANN runtime structure and its performance lifecycle.
• Employ profiling instruments and the Graph Engine for performance evaluation and refinement.
• Develop and optimize proprietary operators utilizing TIK and TVM.
• Address memory constraints and augment model throughput for government applications.

Instructional Methodology

• Interactive presentations and facilitated discussions.
• Practical laboratories incorporating real-time profiling and operator calibration.
• Refinement exercises utilizing edge-case deployment scenarios for government sectors.

Instructional Adaptation Options

• To request a customized training curriculum for this module, please contact the provider for coordination.

The Compute Architecture for Neural Networks (CANN) Software Development Kit offers robust mechanisms for the deployment and optimization of real-time artificial intelligence applications in computer vision and natural language processing, particularly on Huawei Ascend infrastructure.

This instructor-led, live training course, available in online or on-site formats, is designed for intermediate-level AI practitioners seeking to build, deploy, and optimize vision and language models using the CANN SDK for production use cases for government.

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

• Deploy and optimize CV and NLP models using CANN and AscendCL.
• Leverage CANN tools to convert models and integrate them into live operational pipelines.
• Enhance inference performance for tasks such as detection, classification, and sentiment analysis.
• Construct real-time CV/NLP pipelines suitable for edge or cloud-based deployment scenarios for government.

Course Format

• Interactive lectures and technical demonstrations.
• Practical laboratory exercises focused on model deployment and performance profiling.
• Design of live pipelines utilizing authentic CV and NLP use cases.

Customization Options

• To request tailored training aligned with specific operational needs for government, please contact the program office to arrange.

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

This instructor-led, live training (available online or onsite) is designed for advanced system developers seeking to build, deploy, and tune custom operators for AI models using CANN’s TIK programming model and TVM compiler integration.

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

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

Format of the Course

• Interactive instruction and practical demonstration.
• Hands-on coding of operators using TIK and TVM pipelines.
• Testing and tuning on Ascend hardware or simulation environments.

Course Customization Options

• To request a customized training for government, please contact us to arrange details.

Integrate the transformative capabilities of AI with the agility of edge computing in this comprehensive course. Learn to deploy AI models directly on edge devices, progressing from foundational CNN architectures to advanced knowledge distillation and federated learning. This practical training equips you with the necessary skills to optimize AI performance for real-time processing and decision-making at the edge, supporting mission-critical operations for government.

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