Under the hood of high-performance AI lies CANN (Compute Architecture for Neural Networks) — the software foundation powering Huawei’s Ascend chips and the minds behind them.
These instructor-led courses peel back the layers of the Compute Architecture for Neural Networks, exploring how CANN bridges algorithms and silicon through graph optimization, kernel fusion, and hardware-aware scheduling.
Whether you’re building inference engines, tuning custom operators, or porting deep learning models to run at the edge, you’ll gain practical insight into maximizing performance on Ascend processors.
Train live online via an interactive remote desktop, or join onsite sessions in Leiden — either at your organization’s premises or a NobleProg training center — featuring labs that simulate production-grade acceleration and deployment pipelines.
Also known as Ascend CANN or Huawei CANN, this training equips developers, engineers, and AI infrastructure teams to get the most from hardware-aware intelligence.
NobleProg – Your Local Training Provider
Leiden
Golden Tulip/Tulip Inn Leiden Centre, Schipholweg 3, Leiden, Netherlands, 2316XB
The 4-star Golden Tulip Leiden Center is located right next to the Tulip Inn Leiden Center hotel; together they accommodate 7 stars under one roof. The hotels are ideally located with Leiden Central Station directly opposite and many motorways within easy reach. A beautiful location in the center of the historic city of Leiden full of museums and picturesque spots. Experience, enjoy and be inspired.
Golden Tulip & Tulip Inn Leiden Center have a large diversity of hotel rooms; from comfortable and modern furnished standard rooms to luxurious executive rooms. In total there are 155 rooms. Furthermore, the hotels have a renovated restaurant called "Rubens", a cozy bar / lounge and an extensive meeting & conference center.
The 6 multifunctional rooms make Golden Tulip & Tulip Inn Leiden Center the ideal location for small and medium-sized meetings. The rooms have a capacity of 4 to 100 people. The meeting rooms offer countless possibilities in terms of setup and technical facilities. Convenience, efficiency, hospitality and professionalism are paramount. All rooms have air conditioning, free wireless internet and daylight.
Until the early 19th century, fishing in Noordwijk aan Zee remained the most important form of income. Later the population started to focus more and more on tourism. More than 1 million overnight stays take place every year. Noordwijk aan Zee consists of several districts and is located on the dunes. There are various catering establishments such as hotels, entertainment centers and restaurants (also on the beach) and there is a shopping center that has a Sunday opening. Every year events take place on the boulevard around the lighthouse on the Vuurtorenplein. The municipality has a KNRM rescue station and a reformed church (1647) with pulpit from the 17th century.
Since the merger with the Noordwijkerhout municipality, the municipality consists of four centers.
Noordwijk aan Zee, traditionally a fishing village, has become a seaside resort with a long coastal strip of approximately 13 km. . Noordwijk aan Zee has two boulevards, both of which are named after a queen, Queen Wilhelmina Boulevard and Queen Astrid Boulevard.
Noordwijk-Binnen radiates the tranquility of earlier centuries in the old core. In 1992 the old village center was designated as a protected village view under the Monuments Act.
Noordwijkerhout, a village and former municipality northeast of Noordwijk..Noordwijk aan Zee is rated as the 12th richest location in the Netherlands. Beer magnate Freddy Heineken has built a villa there with the characteristic green roof.
The Two Brothers Noordwijk Beach Hotel is located on the boulevard of Noordwijk with a view of the village and the sea and has several conference rooms and training rooms that make it the perfect place for business meetings and stimulating training. Noordwijk is a 30-minute drive from Amsterdam and The Hague and only 20 minutes from Leiden.
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 optimize 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.
Optimize 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 Customization Options
To request a customized training for this course based on your infrastructure or datasets, please contact us 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 beginner-level to intermediate-level technical professionals who wish 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.
The CANN SDK (Compute Architecture for Neural Networks) provides powerful deployment and optimization tools for real-time AI applications in computer vision and NLP, especially on Huawei Ascend hardware.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI practitioners who wish to build, deploy, and optimize vision and language models using the CANN SDK for production use cases.
By the end of this training, participants will be able to:
Deploy and optimize CV and NLP models using CANN and AscendCL.
Use CANN tools to convert models and integrate them into live pipelines.
Optimize inference performance for tasks like detection, classification, and sentiment analysis.
Build real-time CV/NLP pipelines for edge or cloud-based deployment scenarios.
Format of the Course
Interactive lecture and demonstration.
Hands-on lab with model deployment and performance profiling.
Live pipeline design using real CV and NLP use cases.
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.
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 ops 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.
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 where compute and memory are constrained.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and integrators who wish to deploy and optimize 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 Ascend 310 using CANN tools.
Build lightweight inference pipelines using MindSpore Lite and AscendCL.
Optimize model performance for limited compute and memory environments.
Deploy and monitor AI applications in real-world edge use cases.
Format of the Course
Interactive lecture and demonstration.
Hands-on lab work with edge-specific models and scenarios.
Live deployment examples on virtual or physical edge hardware.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing toolkit used to compile, optimize, and deploy 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 works with frameworks like MindSpore, TensorFlow, and PyTorch.
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.
Convert and deploy a simple AI model to Ascend hardware.
Gain foundational knowledge for future CANN optimization or integration projects.
Format of the Course
Interactive lecture and discussion.
Hands-on labs with simple model deployment.
Step-by-step walkthrough of the CANN toolchain and integration points.
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 that allows 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 optimize inference performance using CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator development.
By the end of this training, participants will be able to:
Understand CANN's runtime architecture and performance lifecycle.
Use profiling tools and Graph Engine for performance analysis and optimization.
Create and optimize custom operators using TIK and TVM.
Resolve memory bottlenecks and improve model throughput.
Format of the Course
Interactive lecture and discussion.
Hands-on labs with real-time profiling and operator tuning.
Optimization exercises using edge-case deployment examples.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
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.
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