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Huawei HCIA-AI H13-311 Study Guide

Huawei Certified ICT Associate-Artificial Intelligence (HCIA-AI) H13-311

Huawei HCIA-AI, exam H13-311 V4.0, tests a foundation in artificial intelligence and the skills to take part in AI projects. It covers machine learning, deep learning and foundation models, AI development frameworks with PyTorch, the AI and large model business process, and cutting-edge AI applications. It suits engineers, developers and students starting a career in AI.

  • Exam code H13-311
  • Associate level
  • 6 exam domains

This guide is free, with no sign-up. It explains every Huawei HCIA-AI H13-311 exam topic in plain English, one chapter at a time. Read them in order or jump straight to the topic you need.

  • 6chapters
  • 12topics
  • 4diagrams and exhibits
  • 1 h 3 minfast track
Start with AI
  • Every topic follows the same simple pattern: what it is, how it works, common mistakes
  • Diagrams and real command output where a picture explains it best
  • Exam tips and worked subnetting and IPv6 practice, with answers

How the exam is weighted

Each domain is worth this share of the exam, so spend your study time in proportion. Select a domain to open its chapter.

Chapters

Open a chapter to see its topics and how long each takes.

1AI2 topics · 10 min fast trackWhat AI is, its schools and technologies, DeepSeek, AI applications and the disputes around AI.
  1. 1AI Description and AI Technologies5 min
  2. 2DeepSeek, AI Applications and the Future of AI5 min
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2Machine Learning2 topics · 10 min fast trackLearning types, the ML process, gradient descent, hyperparameters and the common ML algorithms.
  1. 1Machine Learning Algorithms, Types and Process5 min
  2. 2Key Machine Learning Methods and Common Algorithms5 min
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3Basics of Deep Learning and Foundation Models3 topics · 17 min fast trackPerceptrons, neural network training, CNNs, RNNs and LSTMs, Transformers and foundation models.
  1. 1Perceptron and Fully-connected Neural Networks5 min
  2. 2CNN and RNN Architectures6 min
  3. 3Transformer and Foundation Model Infrastructure6 min
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4AI Development Framework2 topics · 10 min fast trackWhat AI frameworks do, tensors, graphs, autograd, PyTorch and the development process.
  1. 1AI Frameworks and Development Basics5 min
  2. 2PyTorch and AI Application Development5 min
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5AI Business Process2 topics · 11 min fast trackThe AI project lifecycle, the large model process, RAG, agents and prompt engineering basics.
  1. 1AI and Large Model Business Processes5 min
  2. 2Using Large Models and Prompt Engineering6 min
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6Cutting-edge AI Applications1 topic · 5 min fast trackVoice assistants, smart homes, vehicles, recommendation, robots and AI4Science.
  1. 1Cutting-edge AI Application Scenarios5 min
Read the chapter overview →

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