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

  • Exam Code: H13-311-ENU
  • Exam Name: HCIA-AI (Huawei Certified ICT Associate-Artificial Intelligence)
  • Updated: Sep 07, 2026
  • Q & A: 175 Questions and Answers

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Understanding functional and technical aspects of Overview of artificial intelligence

The following will be discussed in HUAWEI H13-311 exam dumps:

  • Advancement of AI Industries
  • Artificial intelligence Society in the Future
  • The Past, Present, and Future of AI
  • Human-Machine Relationship in the Era of AI
  • Equity and Equity in the Era of AI
  • Key Planning of AI in the World
  • Artificial intelligence Governance

Who should take the Huawei Certified ICT Associate-Artificial Intelligence

Engineers who need to master AI technologies, learn and use deep learning algorithms, and master Huawei AI-related product technologies.

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Understanding functional and technical aspects of Overview of Deep Learning

The following will be discussed in HUAWEI H13-311 exam dumps:

  • Characterizing the TensorFlow Input Node
  • TensorFlow Development Environment Setup
  • TensorFlow Overview
  • Upgrading Functions and Objectives
  • Utilizing the Model
  • Characterizing the Learning Parameter Variable
  • Instating All Variables
  • Characterizing the Operation
  • TensorFlow Modules
  • TensorFlow Basics
  • Repeat and Update Parameters to the Optimal Solution
  • Testing the Model
  • TensorFlow Characteristics
  • Fundamental Development Steps Using TensorFlow

Understanding functional and technical aspects of Essential mathematics knowledge and pre-knowledge for Deep Learning

The following will be discussed in HUAWEI H13-311 exam dumps:

  • Bayesian Rules
  • Follow Operator
  • Uncommon Matrices
  • Flood and Underflow
  • Minor Probability
  • Moore-Penrose Pseudoinverse
  • Restrictive Probability
  • Linear Algebra
  • Particular Value Decomposition
  • Likelihood Distribution
  • Likelihood Theory and Information Theory
  • Basic Probability Distribution
  • Organized Statistical Model
  • Model: Principal Component Analysis
  • Ceaseless Variable
  • Irregular Variables
  • Numeric Calculation
  • Inclination Based Optimization Method
  • Sick Condition
  • Imperative Optimization
  • Model: Linear Least Squares
  • Assumption, Variance, and Covariance
  • Data Theory
  • Freedom and Conditional Independence
  • Eigendecomposition
  • Determinants

Huawei H13-311-ENU Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Development Frameworks12%- TensorFlow basics and usage
- Huawei MindSpore framework introduction
Topic 2: Machine Learning Overview20%- Model training and evaluation
- Basic concepts and classification
- Common algorithms and models
Topic 3: Huawei AI Platform & Applications8%- Huawei Cloud EI and ModelArts
- Ascend computing platform and Atlas series
- Typical AI application scenarios
Topic 4: Artificial Intelligence Overview15%- AI technology and application fields
- Huawei AI strategy and full-stack architecture
- History and development of AI
Topic 5: Mathematics and Python Basics20%- Linear algebra, probability and statistics
- Python programming fundamentals
- Data processing and visualization
Topic 6: Deep Learning Overview25%- Neural network fundamentals
- Training mechanisms and optimization
- CNN, RNN and basic architectures

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