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

H13-311-ENU

Exam Code: H13-311-ENU

Exam Name: HCIA-AI (Huawei Certified ICT Associate-Artificial Intelligence)

Updated: Jul 26, 2026

Q & A: 175 Questions and Answers

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How much Huawei Certified ICT Associate-Artificial Intelligence cost

Huawei Certified ICT Associate-Artificial Intelligence cost is $250 USD

Topics of Huawei Certified ICT Associate-Artificial Intelligence

The following will be discussed in HUAWEI H13-311 practice exam and HUAWEI H13-311 practice exams:

  • Python programming nuts and bolts
  • Outline of computerized reasoning
  • Outline of TensorFlow, programming nuts and bolts, and techniques for utilizing TensorFlow programming for picture acknowledgment, discourse acknowledgment, and human-machine exchange
  • Fundamental science information and pre-information for Deep Learning
  • Outline of Huawei cloud EI
  • Outline of Deep Learning
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Huawei H13-311-ENU Exam Syllabus Topics:
SectionObjectives
AI Development and Huawei AI Ecosystem- Data processing and AI pipeline
  • 1. Data preprocessing and feature engineering
    • 2. Model evaluation and optimization basics
      - Huawei AI platform and tools
      • 1. MindSpore framework overview
        • 2. Model training and deployment workflow
          Deep Learning Fundamentals- Common deep learning models
          • 1. RNN basics for sequence modeling
            • 2. CNN basics for computer vision
              - Neural networks
              • 1. Perceptron and multilayer networks
                • 2. Activation functions and backpropagation
                  Machine Learning Basics- Unsupervised learning
                  • 1. Dimensionality reduction
                    • 2. Clustering algorithms
                      - Supervised learning
                      • 1. Regression models
                        • 2. Classification models
                          Artificial Intelligence Fundamentals- Mathematics for AI
                          • 1. Probability and statistics fundamentals
                            • 2. Linear algebra basics
                              - AI concepts and basic principles
                              • 1. AI application scenarios and industry overview
                                • 2. Definition of AI and key terminology
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