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 Trojmiasto — 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
Gdynia
Hotel Nadmorski, Ejsmonda 2, Gdynia, Poland, 81-409
The training room is located just 3 kilometers from the PKP/PKS Station in Gdynia, making it easily accessible for participants traveling by train or bus. Additionally, it is only 400 meters away from the bus stop, facilitating access even for those using public transportation. It is equipped with necessary training tools such as a projector, screen, and flipchart, providing comfortable conditions for both participants and the trainer.
Gdańsk
Hotel Fahrenheit, Grodzka 19, Gdańsk, Poland, 80-841
The training room is located in the very heart of the picturesque Gdansk Old Town, making the surroundings not only inspiring but also exceptionally attractive for participants. Within close proximity, you can find the railway and bus stations, facilitating arrival for those traveling by both train and bus. Additionally, the airport and port are also within reach, making this location convenient for individuals coming from distant places, both domestically and internationally.
This instructor-led training in Trojmiasto guides intermediate AI engineers to build and optimize neural network models using the Huawei Ascend platform and CANN toolkit. Participants will configure environments, develop applications with MindSpore, and deploy to edge or cloud settings.
This instructor-led live training in Trojmiasto explores Huawei's AI stack, from the CANN SDK to the MindSpore framework. It helps beginners and intermediate professionals understand how these components integrate on Ascend hardware for lifecycle management and deployment.
This instructor-led training in Trojmiasto covers deploying and optimizing CV and NLP models using the CANN SDK for Ascend hardware. Participants will learn to convert models, integrate them into live pipelines, and enhance inference performance for real-time detection and analysis.
This instructor-led, live training in Trojmiasto equips advanced developers with the skills to build, deploy, and tune custom AI operators. Participants will master CANN TIK and Apache TVM integration, enabling advanced optimization and scheduling on Huawei Ascend hardware for real-world performance.
This instructor-led, live training in Trojmiasto covers the core concepts and hands-on fundamentals of deploying AI models on Ascend edge devices using the CANN toolkit, helping participants build practical skills for compiling, optimizing, and managing constrained environments.
This live training in Trojmiasto introduces the CANN toolkit for AI framework developers. Learn to set up environments, convert models, and deploy applications on Ascend hardware using MindSpore, TensorFlow, or PyTorch, covering the full workflow from training to inference.
Optimize neural network inference performance on Ascend AI processors with this advanced, instructor-led training in Trojmiasto. Explore CANN's runtime architecture, leveraging the Graph Engine, TIK, and TVM for profiling, custom operator development, and memory bottleneck resolution.
This live training in Trojmiasto guides intermediate AI developers through deploying models on Ascend processors using the CANN toolkit. Learn to convert frameworks like PyTorch and TensorFlow, optimize performance, and debug issues for efficient edge and cloud inference scenarios.
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