Cursusaanbod

Introduction to Huawei’s AI Ecosystem

  • Ascend AI hardware: 310, 910, and 910B chips
  • MindSpore, CANN, and supporting tools
  • AI development workflow: training to deployment

Understanding the CANN Toolkit

  • What is CANN and why it matters
  • Overview of core components (ATC, AscendCL, operator libraries)
  • Role of CANN in AI inference pipelines

Getting Started with MindSpore and CANN

  • Setting up the environment (MindSpore + CANN + Python)
  • Training a basic model in MindSpore
  • Exporting and converting the model using ATC

Running Inference on Ascend Devices

  • Using the OM model with AscendCL or Python APIs
  • Basic input/output preprocessing
  • Validating model outputs

Working with Other Frameworks

  • Overview of support for TensorFlow, PyTorch, and ONNX
  • Supported operators and limitations
  • Simple model conversion demo (e.g., from ONNX to OM)

Exploring the CANN and MindSpore Developer Ecosystem

  • Key resources: documentation, GitHub repositories, sample code
  • MindSpore Hub and model zoo overview
  • Community forums, events, and support channels

Summary and Next Steps

Vereisten

  • Basic understanding of machine learning and deep learning concepts
  • Some programming experience with Python
  • No prior experience with CANN or Ascend hardware required

Audience

  • Machine learning developers exploring deployment workflows
  • Students or researchers new to Huawei’s AI ecosystem
  • AI framework contributors and hobbyists interested in model acceleration
 7 Uren

Leveringsopties

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  • Pre-cursusgesprek met uw trainer
  • Aanpassing van de leerervaring om uw doelen te bereiken -
    • Op maat gemaakte overzichten
    • Praktische, praktische oefeningen met gegevens / scenario's die herkenbaar zijn voor de cursisten
  • Training gepland op een datum naar keuze
  • Gegeven online, op locatie/klaslokaal of hybride door experts die ervaring uit de echte wereld delen

Private Group Prices RRP from €2280 online delivery, based on a group of 2 delegates, €720 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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