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Mirobod

21A, Taras Shevchenko Street, Mirabad, Mirobod, Uzbekistan, 100015

The Centre is located at Taras Shevchenko Street, in the central Mirabad district of Tashkent, Uzbekistan. The location is conveniently placed near the Ming Urik metro station and is also close to the Oybek metro interchange, making it easily accessible by public transport from different parts of the city. The Centre is approximately 5–6 kilometres from Islam Karimov Tashkent International Airport, depending on the route and traffic conditions. The area is well-connected and sits close to key central Tashkent landmarks, business areas, and hospitality options. Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate office.

Subcategories (1)

CANN

CANN

Explore Our Courses

Developing AI Applications with Huawei Ascend and CANN

 21 Hours

Huawei Ascend is a family of AI processors 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 optimise neural network models using Huawei's Ascend platform and the CANN toolkit.

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

  • Set up and configure the CANN development environment.
  • Develop AI applications using MindSpore and CloudMatrix workflows.
  • Optimise performance on Ascend NPUs using custom operators and tiling.
  • Deploy models to edge or cloud environments.

Format of the Course

  • Interactive lecture and discussion.
  • Hands-on use of Huawei Ascend and CANN toolkit in sample applications.
  • Guided exercises focused on model building, training, and deployment.

Course Customisation Options

  • To request a customised training for this course based on your infrastructure or datasets, please contact us to arrange.
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Understanding Huawei’s AI Compute Stack: From CANN to MindSpore

 14 Hours

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

This instructor-led, live training (online or onsite) targets beginner-level to intermediate-level technical professionals who want to understand how the CANN and MindSpore components work together to support AI lifecycle management and infrastructure decisions.

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.

Format of the Course

  • Interactive lecture and discussion.
  • Live system demos 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.
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CANN SDK for Computer Vision and NLP Pipelines

 14 Hours

The CANN SDK (Compute Architecture for Neural Networks) offers powerful deployment and optimisation tools for real-time AI applications in computer vision and natural language processing (NLP), particularly on Huawei Ascend hardware.

This instructor-led, live training (available online or on-site) is designed for intermediate-level AI practitioners who aim to build, deploy, and optimise vision and language models using the CANN SDK for production-grade use cases.

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

  • Deploy and optimise computer vision (CV) and NLP models using CANN and AscendCL.
  • Leverage CANN tools to convert models and integrate them into live pipelines.
  • Optimise inference performance for tasks such as object detection, classification, and sentiment analysis.
  • Construct real-time CV/NLP pipelines tailored for edge or cloud-based deployment scenarios.

Course Format

  • Interactive lectures and demonstrations.
  • Practical labs covering model deployment and performance profiling.
  • Live pipeline design using real-world CV and NLP use cases.

Course Customisation Options

  • To request a customised version of this course, please contact us to arrange the details.
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Building Custom AI Operators with CANN TIK and TVM

 14 Hours

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

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

Upon completing this training, participants will be capable of:

  • Writing and testing custom AI operators using the TIK DSL for Ascend processors.
  • Integrating custom operators into the CANN runtime and execution graph.
  • Utilizing TVM for operator scheduling, auto-tuning, and benchmarking.
  • Debugging and optimizing instruction-level performance for custom computational patterns.

Course Format

  • Interactive lectures and demonstrations.
  • Hands-on coding exercises for operators using TIK and TVM pipelines.
  • Testing and tuning on Ascend hardware or simulators.

Customization Options

  • To request a customized training session, please contact us to make arrangements.
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AI Inference and Deployment with CloudMatrix

 21 Hours

CloudMatrix serves as Huawei's consolidated AI development and deployment platform, engineered to facilitate scalable, production-ready inference pipelines.

This instructor-led live training, available either online or onsite, targets beginner to intermediate-level AI professionals looking to deploy and monitor AI models using the CloudMatrix platform, integrated with CANN and MindSpore.

Upon completing this training, participants will be capable of:

  • Utilizing CloudMatrix for model packaging, deployment, and serving.
  • Converting and optimizing models for Ascend chipsets.
  • Establishing pipelines for both real-time and batch inference tasks.
  • Monitoring deployments and fine-tuning performance within production environments.

Course Format

  • Interactive lectures and discussions.
  • Practical application of CloudMatrix through real-world deployment scenarios.
  • Guided exercises concentrating on conversion, optimization, and scaling.

Customization Options

  • To request tailored training for this course based on your specific AI infrastructure or cloud environment, please reach out to us to arrange.
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CANN for Edge AI Deployment

 14 Hours

Huawei’s Ascend CANN toolkit enables powerful AI inference on edge devices such as the Ascend 310. CANN provides essential tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

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

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

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

Course Format

  • Interactive lectures and live demonstrations.
  • Hands-on lab sessions using edge-specific models and practical scenarios.
  • Live deployment examples on virtual or physical edge hardware.

Course Customisation Options

  • To request a customised version of this course, please contact us to arrange.
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Introduction to CANN for AI Framework Developers

 7 Hours

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 training, available online or onsite, is tailored for beginner-level AI developers seeking to understand how CANN integrates into the model lifecycle from training to deployment, and how it works alongside frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completing this training, participants will be able to:

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

Course Format

  • Interactive lectures and discussions.
  • Practical labs focused on simple model deployment.
  • Step-by-step guidance through the CANN toolchain and integration points.

Course Customization Options

  • For customized training requests, please contact us to arrange details.
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Performance Optimization on Ascend, Biren, and Cambricon

 21 Hours

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:

  • Benchmark models on Ascend, Biren, and Cambricon platforms.
  • Identify system bottlenecks and memory/compute inefficiencies.
  • Apply graph-level, kernel-level, and operator-level optimizations.
  • Tune deployment pipelines to improve throughput and latency.

Course Format

  • Interactive lectures and discussions.
  • Hands-on experience with profiling and optimization tools on each platform.
  • Guided exercises focused on practical tuning scenarios.

Course Customization Options

  • To request a customized training session tailored to your performance environment or model type, please contact us to arrange.
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Optimizing Neural Network Performance with CANN SDK

 14 Hours

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

This instructor-led live training, available both online and on-site, is designed for advanced AI developers and system engineers looking to enhance inference performance using CANN’s sophisticated tools, such as the Graph Engine, TIK, and custom operator development capabilities.

Upon completing this training, participants will be able to:

  • Comprehend CANN’s runtime architecture and its performance lifecycle.
  • Leverage profiling tools and the Graph Engine for performance analysis and optimization.
  • Develop and optimize custom operators utilizing TIK and TVM.
  • Address memory bottlenecks and boost 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

  • To request a tailored version of this course, please contact us to arrange your specific needs.
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Migrating CUDA Applications to Chinese GPU Architectures

 21 Hours

Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide viable alternatives to CUDA, specifically designed for the local AI and high-performance computing (HPC) markets.

This instructor-led live training, available online or on-site, is designed for advanced GPU programmers and infrastructure specialists seeking to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.

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

  • Assess the compatibility of current 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 opportunities across different platforms.
  • Tackle practical challenges related to cross-architecture support and deployment.

Course Format

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

Customization Options

  • For customized training tailored to your specific platform or CUDA project, please contact us to arrange a session.
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Deploying AI Models with CANN and Ascend AI Processors

 14 Hours

CANN (Compute Architecture for Neural Networks) is Huawei’s AI compute stack 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 deploy trained AI models efficiently to Huawei Ascend hardware using the CANN toolkit and tools such as MindSpore, TensorFlow, or PyTorch.

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

  • Understand the CANN architecture and its role in the AI deployment pipeline.
  • Convert and adapt models from popular frameworks to Ascend-compatible formats.
  • Use tools like ATC, OM model conversion, and MindSpore for edge and cloud inference.
  • Diagnose deployment issues and optimize performance on Ascend hardware.

Format of the Course

  • Interactive lecture and demonstration.
  • Hands-on lab work using CANN tools and Ascend simulators or devices.
  • Practical deployment scenarios based on real-world AI models.

Course Customization Options

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

Last Updated:

Upcoming Courses

Developing AI Applications with Huawei Ascend and CANN

2026-08-19 09:30
21 hours
Mirobod
33,896,260 UZS (Online)
36,896,260 UZS (Classroom)

Performance Optimization on Ascend, Biren, and Cambricon

2026-09-02 09:30
21 hours
Mirobod
33,896,260 UZS (Online)
36,896,260 UZS (Classroom)

CANN for Edge AI Deployment

2026-09-16 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

Optimizing Neural Network Performance with CANN SDK

2026-09-30 09:30
14 hours
Mirobod
22,597,506 UZS (Online)
24,597,506 UZS (Classroom)

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