Huawei HCIA-AI study guide
Huawei HCIA-AI · Work through your exam, one topic at a time.
The Huawei Certified ICT Associate (HCIA) is the entry level of Huawei's three-tier Career Certification roadmap, which runs from Associate (HCIA) through Professional (HCIP) to Expert (HCIE). The AI track sits in the same scheme as the named Computing, Datacom and other technology tracks, and is aimed at newcomers who want a recognised, vendor-aligned foundation in artificial intelligence before moving on to professional-level study. Candidates typically include students, career changers, and engineers who work alongside Huawei infrastructure and want a structured vocabulary for AI concepts. Exam content is organised around five areas: an AI overview and Huawei's AI strategy, machine learning fundamentals, deep learning fundamentals, mainstream development frameworks such as TensorFlow and MindSpore, and the Huawei AI computing platform covering Ascend, Atlas and CANN. The Huawei HCIA-AI study guide has 5 sections and about 1,445 words.
01AI Overview and Huawei AI Strategy
The AI Overview and Huawei AI Strategy domain tests whether you can place Huawei products inside a layered AI architecture and pick the layer that owns a given customer requirement. Huawei describes its AI portfolio as full-stack and all-scenario.
286 words, about 1 min02Machine Learning Fundamentals
Machine Learning Fundamentals tests classical ML concepts: problem types, data splitting, generalization, regularization, and evaluation metrics. Expect scenario questions where a metric or split choice decides the answer.
262 words, about 1 min03Deep Learning Fundamentals
Deep Learning Fundamentals tests how neural networks are built and trained: layers, activations, losses, backpropagation, optimizers, and the shape arithmetic that connects them. A dense layer computes y = activation(Wx + b).
308 words, about 2 min04Mainstream AI Development Frameworks (TensorFlow, MindSpore)
This domain compares TensorFlow and MindSpore at the programming-model level: how graphs are built, how gradients are obtained, how models are saved, and how hardware is targeted. Tensors are the core data type; eager execution runs operations immediately.
275 words, about 1 min05Huawei AI Computing Platform (Ascend, Atlas, CANN)
This domain tests the Huawei AI hardware and software stack: which Ascend chip fits training or inference, which Atlas product fits a deployment tier, and what CANN contributes. Ascend 310: inference-focused, low-power AI processor.
314 words, about 2 min