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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.

Biren AI Accelerators are high-performance GPUs designed for artificial intelligence and high-performance computing (HPC) workloads, with robust support for large-scale training and inference.

This instructor-led, live training (available online or on-site) is tailored for intermediate to advanced developers who wish to program and optimize applications using Biren’s proprietary GPU stack, with practical comparisons to CUDA-based environments.

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

• Comprehend Biren GPU architecture and memory hierarchy.
• Establish the development environment and utilize Biren’s programming model.
• Convert and optimize CUDA-style code for Biren platforms.
• Implement performance tuning and debugging techniques.

Format of the Course

• Interactive lecture and discussion sessions.
• Hands-on use of Biren SDK in sample GPU workloads.
• Guided exercises focused on porting and performance tuning.

Course Customization Options

• To request a customized training for government based on your specific application stack or integration needs, please contact us to arrange.

Cambricon MLUs (Machine Learning Units) are specialized AI chips designed to optimize inference and training in edge and data center environments.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware for government applications.

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

• Set up and configure the BANGPy and Neuware development environments for government use.
• Develop and optimize Python- and C++-based models for Cambricon MLUs in alignment with public sector workflows.
• Deploy models to edge and data center devices running Neuware runtime, ensuring compliance with governance standards.
• Integrate machine learning workflows with MLU-specific acceleration features to enhance performance and accountability.

Format of the Course

• Interactive lecture and discussion focused on government applications.
• Hands-on use of BANGPy and Neuware for development and deployment in a public sector context.
• Guided exercises centered on optimization, integration, and testing tailored to government needs.

Course Customization Options

• To request a customized training for this course based on your Cambricon device model or specific use case for government, please contact us to arrange.

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 Ascend CANN toolkit facilitates robust AI inference on edge devices such as the Ascend 310. CANN offers essential tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

This instructor-led, live training (online or onsite) is designed for intermediate-level AI developers and integrators who aim to deploy and optimize models on Ascend edge devices using the CANN toolchain for government applications.

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

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

Format of the Course

• Interactive lecture and demonstration.
• Hands-on laboratory work with models and scenarios specific to edge devices.
• Live deployment examples on virtual or physical edge hardware.

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.

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

This instructor-led, live training (online or onsite) is aimed at advanced-level GPU programmers and infrastructure specialists who wish to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms for government use.

By the end 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 different platforms.
• Address practical challenges in supporting and deploying applications across multiple architectures.

Format of the Course

• Interactive lecture and discussion sessions.
• 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.

Ascend, Biren, and Cambricon are leading AI hardware platforms in China, each offering unique acceleration and profiling tools for production-scale AI workloads.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI infrastructure and performance engineers who wish to optimize model inference and training workflows across multiple Chinese AI chip platforms.

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

• Evaluate models on Ascend, Biren, and Cambricon platforms.
• Identify system bottlenecks and memory/compute inefficiencies.
• Implement graph-level, kernel-level, and operator-level optimizations.
• Adjust deployment pipelines to enhance throughput and reduce latency.

Format of the Course

• Interactive lecture and discussion.
• Practical use of profiling and optimization tools on each platform.
• Guided exercises focused on real-world tuning scenarios.

Course Customization Options

• To request a customized training for government based on your specific performance environment or model type, please contact us to arrange.