Cambricon’s MLU chips are far more than simple processors; they serve as a robust solution for scalable, high-efficiency AI acceleration across cloud, edge, and data center environments.
This instructor-led training program walks engineers and AI developers through the Cambricon stack, covering everything from deploying deep learning models to optimizing performance on MLU hardware.
Courses are available as live online sessions via interactive remote desktop, or as onsite training in Copenhagen. These hands-on labs are designed to reflect the real-world AI challenges that Cambricon addresses.
Whether you are expanding an AI laboratory or preparing your data center team for the future, onsite sessions can be held at your facility in Copenhagen or within NobleProg training centers tailored for immersive technical learning.
Known also as Cambricon AI, the MLU accelerator, or the Machine Learning Unit, this training supports teams looking to build AI infrastructure that goes beyond the traditional GPU approach.
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.
Enhance AI workloads on Ascend, Biren, and Cambricon through this practical training in Copenhagen. Master the skills to benchmark models, pinpoint bottlenecks, and deploy graph, kernel, and operator-level optimizations. Refine deployment pipelines to boost throughput and latency performance across these leading platforms.
Transition CUDA applications to Chinese GPU structures such as Huawei Ascend and Biren within Copenhagen. This guided training supports advanced programmers through code adaptation and performance refinement, featuring practical labs for migrating CUDA codebases to emerging SDKs.
This live, instructor-led course in Copenhagen empowers developers to construct and deploy AI models using BANGPy and Neuware on Cambricon MLUs. Learners will configure their environments, create optimized models, and integrate MLU acceleration capabilities into edge and data center applications.
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