Behind the scenes of high-performance artificial intelligence lies CANN (Compute Architecture for Neural Networks) — the core software framework driving Huawei’s Ascend chips and the intellectual logic underpinning them.
Through these instructor-led courses, we unravel the complexities of the Compute Architecture for Neural Networks, examining how CANN serves as the bridge between algorithms and silicon via graph optimization, kernel fusion, and hardware-aware scheduling.
Whether you are developing inference engines, refining custom operators, or migrating deep learning models for edge execution, you will acquire practical insights into optimizing performance on Ascend processors.
Engage in live online training via an interactive remote desktop, or participate in onsite sessions in Copenhagen — either at your organization’s location or a NobleProg training facility — complete with labs that emulate production-grade acceleration and deployment workflows.
Also recognized as Ascend CANN or Huawei CANN, this program prepares developers, engineers, and AI infrastructure teams to fully leverage hardware-aware intelligence.
You can also take bus 26 or 7A and get off around Vesterbros Torv; from there it is a short walk.
By bus
Useful nearby stops include:
Vesterbros Torv (Vesterbrogade) — about 1 minute from the area.
Frederiksberg Allé (Vesterbrogade) — nearby.
Trommesalen (Vesterbrogade) — nearby.
Bus 26 and 7A serve the Vesterbrogade corridor.
København, Copenhagen
NobleProg København, Bredgade 37, København K, denmark, 1260
Near Amalienborg Palace & Royal Theatre.
If you arrive by train
If you arrive at Copenhagen Central Station (København H):
Walk to København H Metro.
Take the M3 or M4 metro toward Kongens Nytorv.
Get off at Kongens Nytorv.
Walk north toward Nyhavn, then continue along Bredgade.
Bredgade 37 is about 500 m / 6 minutes' walk from Kongens Nytorv.
Another easy option
Marmorkirken (Marble Church) Metro Station is also very close to Bredgade 37. The nearby Bredgade area is about 2 minutes' walk from Marmorkirken station.
By bus
There are bus stops around Dronningens Tværgade / Bredgade, so you can also travel by bus and walk the final few minutes.
This instructor-led course in Copenhagen guides intermediate AI engineers in constructing and optimizing neural network models using the Huawei Ascend platform and CANN toolkit. Learners will set up environments, develop applications with MindSpore, and deploy to edge or cloud configurations.
This live, instructor-led course in Copenhagen delves into Huawei's AI architecture, ranging from the CANN SDK to the MindSpore framework. It is tailored for beginners and intermediate professionals aiming to comprehend how these elements function together on Ascend hardware to streamline lifecycle management and deployment.
This instructor-led training in Copenhagen focuses on deploying and optimizing CV and NLP models using the CANN SDK for Ascend hardware. Participants will gain the skills to convert models, integrate them into live pipelines, and improve inference performance for real-time detection and analysis.
This live, instructor-led training in Copenhagen empowers advanced developers with the necessary skills to build, deploy, and optimise custom AI operators. By mastering the integration of CANN TIK and Apache TVM, participants will be able to perform advanced optimisation and scheduling on Huawei Ascend hardware to achieve superior real-world performance.
This instructor-led, live training in Copenhagen explores the fundamental concepts and practical aspects of deploying AI models on Ascend edge devices using the CANN toolkit, enabling participants to develop proficiency in compiling, optimizing, and managing applications within constrained environments.
This live training on Copenhagen introduces the CANN toolkit to AI framework developers. You will learn to configure environments, convert models, and deploy applications on Ascend hardware using MindSpore, TensorFlow, or PyTorch, covering the entire workflow from training to inference.
Elevate neural network inference performance on Ascend AI processors through this advanced, instructor-led training in Copenhagen. Delve into CANN's runtime architecture, utilizing the Graph Engine, TIK, and TVM to profile, develop custom operators, and resolve memory constraints.
This live training in Copenhagen supports intermediate AI developers in deploying models on Ascend processors via the CANN toolkit. It covers converting frameworks like PyTorch and TensorFlow, optimizing performance, and debugging issues to ensure efficient edge and cloud inference.
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