AI Inference and Deployment with CloudMatrix Training Course

Huawei Ascend is a suite of AI processors engineered for high-performance training and inference tasks.

This instructor-led live training session (available online or on-site) targets intermediate-level data scientists and AI engineers interested in developing and optimizing neural network models using Huawei's CANN toolkit and Ascend platform.

Upon completion, participants will be capable of:

• Configuring and setting up the CANN development environment.
• Building AI applications utilizing CloudMatrix workflows and MindSpore.
• Enhancing performance on Ascend NPUs through tiling and custom operators.
• Deploying models to cloud or edge environments.

Course Format

• Interactive discussions and lectures.
• Practical application of Huawei Ascend and the CANN toolkit in sample projects.
• Guided exercises centered on deployment, training, and model construction.

Customization Options

• For tailored training aligned with your specific infrastructure or datasets, please reach out to arrange a session.

CANN (Compute Architecture for Neural Networks) serves as Huawei's AI compute infrastructure designed for deploying and enhancing AI models on Ascend AI processors.

This guided, live training session (available online or at your location) targets intermediate AI developers and engineers seeking to efficiently deploy trained models onto Huawei Ascend hardware utilizing the CANN toolkit alongside tools like MindSpore, TensorFlow, or PyTorch.

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

• Grasp the CANN architecture and its function within the AI deployment workflow.
• Transform and adapt models from leading frameworks into Ascend-compatible formats.
• Leverage tools such as ATC, OM model conversion, and MindSpore for both edge and cloud inference.
• Identify deployment challenges and enhance performance on Ascend hardware.

Course Format

• Interactive lectures combined with practical demonstrations.
• Hands-on exercises using CANN tools with Ascend simulators or physical devices.
• Real-world deployment scenarios grounded in actual AI models.

Customization Options for the Course

• For customized training arrangements, please reach out to us to coordinate.

This instructor-led, live training in Argentina (online or onsite) is designed for beginner to intermediate AI engineers and software developers who wish to gain a foundational understanding of AI engineering principles and practices.

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

• Grasp the fundamental concepts and technologies underlying AI and machine learning.
• Develop basic machine learning models using TensorFlow and PyTorch.
• Utilize AI techniques to resolve practical issues in software development.
• Manage and sustain AI projects by adhering to AI engineering best practices.
• Identify the ethical implications and responsibilities associated with developing AI systems.

This two-day, practical program provides participants with the skills to utilize Generative AI tools effectively, safely, and consistently within technical and operational contexts. The training emphasizes transforming AI into a dependable daily assistant for drafting and enhancing documentation, organizing requirements, speeding up analysis and reporting, aiding in problem-solving, and improving cross-functional communication. Attendees will master established prompting patterns, validation methods to minimize errors and "hallucinations," and lightweight governance practices to safeguard confidential data and intellectual property. The course aims to deliver immediately applicable templates, workflows, and a repeatable methodology for AI-assisted work.

This instructor-led, live training in Argentina (online or onsite) is tailored for AI professionals and software developers at intermediate to advanced levels who intend to build smart applications using AI and ML.

Upon completing this training, participants will be able to:

• Understand the advanced concepts and technologies behind AI and ML.
• Analyze and visualize data to inform AI/ML model development.
• Build, train, and deploy AI/ML models effectively.
• Create intelligent applications that can solve real-world problems.
• Evaluate the ethical implications of AI applications in various industries.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing toolkit designed to compile, optimize, and deploy AI models on Ascend AI processors.

This instructor-led live training, available both online and onsite, targets beginner-level AI developers looking to understand how CANN integrates into the model lifecycle—from training to deployment—and how it works with frameworks such as MindSpore, TensorFlow, and PyTorch.

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

• Grasp the purpose and architecture of the CANN toolkit.
• Set up a development environment using CANN and MindSpore.
• Convert and deploy a simple AI model to Ascend hardware.
• Acquire foundational knowledge to support future CANN optimization or integration projects.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on simple model deployment.
• Step-by-step walkthroughs of the CANN toolchain and integration points.

Course Customization Options

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

Huawei's Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. CANN offers the necessary tools to compile, optimize, and deploy models in environments where computational power and memory are limited.

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 completion of this training, participants will be able to:

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines utilizing MindSpore Lite and AscendCL.
• Enhance model performance for scenarios with restricted compute and memory.
• Deploy and monitor AI applications in practical edge use cases.

Course Format

• Interactive lectures and demonstrations.
• Hands-on labs featuring edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Course Customization Options

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

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

This instructor-led, live training (available online or onsite) targets beginner to intermediate technical professionals seeking to comprehend how CANN and MindSpore components collaborate to manage the AI lifecycle and support infrastructure decisions.

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

• Comprehend the layered architecture of Huawei’s AI compute stack.
• Recognize how CANN facilitates model optimization and hardware-level deployment.
• Assess the MindSpore framework and toolchain in comparison to industry alternatives.
• Position Huawei's AI stack within enterprise or cloud/on-premises environments.

Course Format

• Interactive lectures and discussions.
• Live system demonstrations and case-based walkthroughs.
• Optional guided labs covering the model flow from MindSpore to CANN.

Course Customization Options

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

The CANN SDK (Compute Architecture for Neural Networks) serves as Huawei’s foundational AI compute platform, enabling developers to refine and maximize the performance of neural networks deployed on Ascend AI processors.

This instructor-led live training, available both online and onsite, targets advanced AI developers and system engineers looking to boost inference performance through CANN’s sophisticated toolset, which includes the Graph Engine, TIK, and custom operator development capabilities.

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

• Comprehend the runtime architecture and performance lifecycle of CANN.
• Utilize profiling tools and the Graph Engine for effective performance analysis and optimization.
• Develop and optimize custom operators using TIK and TVM.
• Address memory bottlenecks and enhance model throughput.

Course Format

• Interactive lectures and discussions.
• Practical labs featuring real-time profiling and operator tuning.
• Optimization exercises based on edge-case deployment scenarios.

Customization Options for the Course

• For customized training arrangements, please reach out to us.

The CANN SDK (Compute Architecture for Neural Networks) delivers robust deployment and optimization capabilities for real-time AI solutions in computer vision and natural language processing, particularly on Huawei Ascend hardware.

This instructor-led live training, available online or onsite, targets intermediate-level AI professionals looking to construct, deploy, and refine vision and language models using the CANN SDK for real-world production scenarios.

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

• Deploy and optimize computer vision and NLP models utilizing CANN and AscendCL.
• Leverage CANN utilities to transform models and seamlessly integrate them into live processing pipelines.
• Enhance inference performance for applications such as detection, classification, and sentiment analysis.
• Construct real-time CV and NLP pipelines suitable for edge or cloud deployment environments.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical laboratory sessions focused on model deployment and performance profiling.
• Designing live pipelines through real-world CV and NLP use cases.

Course Customization Options

• For personalized training arrangements, please contact us directly.

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

This instructor-led, live training session (available online or on-site) targets advanced system developers looking to construct, deploy, and fine-tune custom operators for AI models using CANN’s TIK programming model alongside TVM compiler integration.

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

• Develop and test custom AI operators utilizing the TIK DSL for Ascend processors.
• Seamlessly integrate custom operations 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.

Course Format

• Interactive lectures combined with live demonstrations.
• Hands-on coding exercises for operators using TIK and TVM pipelines.
• Practical testing and tuning on Ascend hardware or simulators.

Course Customization Options

• To request a customized training version of this course, please reach out to us to arrange.

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

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

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 and identify optimization points across platforms.
• Address practical challenges in cross-architecture support and deployment.

Format of the Course

• Interactive lecture and discussion.
• 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 platform or CUDA project, please contact us to arrange.

This instructor-led, live training in Argentina (online or onsite) is aimed at beginner-level IT professionals who wish to gain a foundational understanding of intelligent applications and how they can be applied in various industries.

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

• Understand the history, principles, and impact of artificial intelligence.
• Identify and apply different machine learning algorithms.
• Manage and analyze data effectively for AI applications.
• Recognize the practical applications and limitations of AI in different sectors.
• Discuss the ethical considerations and societal implications of AI technology.

This instructor-led live training in Argentina (online or onsite) is designed for intermediate to advanced data scientists, engineers, and AI practitioners who wish to master the intricacies of intelligent applications and leverage them to solve complex, real-world problems.

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

• Implement and analyze deep learning architectures.
• Apply machine learning at scale in a distributed computing environment.
• Design and execute reinforcement learning models for decision-making.
• Develop sophisticated NLP systems for language understanding.
• Utilize computer vision techniques for image and video analysis.
• Address ethical considerations in the development and deployment of AI systems.

Ascend, Biren, and Cambricon represent some of the foremost AI hardware ecosystems in China, each providing distinct acceleration capabilities and profiling utilities designed for large-scale AI production environments.

This instructor-led live training, available either online or onsite, targets experienced AI infrastructure and performance engineers who aim to enhance model inference and training workflows across various Chinese AI chip architectures.

Upon completing this training, participants will be equipped to:

• Execute benchmarks on Ascend, Biren, and Cambricon platforms.
• Diagnose system bottlenecks and identify inefficiencies in memory and compute resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Refine deployment pipelines to significantly boost throughput and reduce latency.

Training Format

• Engaging lectures paired with interactive discussions.
• Practical application of profiling and optimization tools specific to each platform.
• Guided exercises centered on real-world tuning scenarios.

Customization Options

• For tailored training based on your specific performance environment or model architecture, please contact us to arrange a session.