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H13-321_V2.0 HCIP-AI-EI Developer V2.0 Exam Dumps

June 26,2024

For those preparing for the H13-321_V2.0 HCIP-AI-EI Developer V2.0 exam, Passcert has recently released the most updated version of their H13-321_V2.0 HCIP-AI-EI Developer V2.0 Exam Dumps to assist in your preparation process. This latest version of the H13-321_V2.0 HCIP-AI-EI Developer V2.0 Exam Dumps encompasses a wide range of real questions and answers that you might encounter during the actual exam. The use of the latest H13-321_V2.0 HCIP-AI-EI Developer V2.0 Exam Dumps from Passcert as part of your study strategy can dramatically improve your understanding of the subject matter, and ultimately, increase your chances of passing the exam successfully.

H13-321_V2.0 HCIP-AI-EI Developer V2.0 Exam Dumps

HCIP-AI-EI Developer Certification

Passing the HCIP-AI-EI Developer V2.0 certification will indicate that you: 1) have mastered the basic principles, architecture and programming of artificial intelligence technology in the field of image processing. Speech processing and natural language processing; 2) are able to develop AI models using python, TensorFlow and Huawei ModelArts; 3) competent for senior image processing engineers, speech recognition engineers, natural language processing engineers and other positions.

Huawei HCIP-AI-EI Developer V2.0 Certification Exam

Certification Details	Information
Certification Program	HCIP-AI-EI Developer V2.0
Exam Code	H13-321
Exam Name	HCIP-AI-EI Developer V2.0
Exam Duration	90 minutes
Pass Score/ Total Score	600/1000
Exam Format	Single-answer Question, Multiple-answer Question, True or false, Short Response Item, Drag and Drop Item
Exam Cost	300USD

Key Points Percentage

Key Points	Percentage
Neural Network Basics	4%
Image Processing Theory and Applications	26%
Speech Processing Theory and Applications	10%
Natural Language Processing Theory and Applications	10%
Overview of Huawei's AI Development Strategy and Full-Stack, All-Scenario AI Portfolio	2%
Overview of ModelArts	4%
Image Processing Lab Guide	12%
Speech Processing Lab Guide	12%
Natural Language Processing Lab Guide	10%

HCIP-AI-EI Developer V2.0 Exam Content

1. Neural Network Basics (4%)

1.1 Deep Learning Basics

1.2 Artificial Neural Network

1.3 Training Neural Network

1.4 Architecture Design of Neural Networks

2. Image Processing Theory and Applications (26%)

2.1 Computer Vision Overview

2.2 Digital Image Processing Fundamentals

2.3 Image Preprocessing Technology

2.4 Basic Tasks of Image Processing

2.5 Feature Extraction and Traditional Methods

2.6 Deep Learning and Convolution Neural Network

2.7 Object detection and object segmentation

3. Speech Processing Theory and Applications (10%)

3.1 Speech Processing

3.2 Speech Recognition

3.3 Text-to-Speech Synthesis

3.4 Traditional Acoustic Model GMM-HMM

3.5 Hybrid Model DNN-HMM

3.6 Advanced Speech Model

4. Natural Language Processing Theory and Applications (10%)

4.1 Introduction to NLP

4.2 Knowledge Required

4.3 Key Tasks

4.4 Applications

5. Introduction to Huawei AI Development Strategy and Full-Stack All-Scenario Solutions (2%)

5.1 AI: New General Purpose Technology

5.2 10 Changes That Will Define the Future

5.3 Huawei's AI Portfolio

6. Overview of ModelArts (4%)

7. Image Processing Lab Guide (12%)

7.1 Image Data Preprocessing

7.2 HUAWEI CLOUD EI Image Tag Service

7.3 HUAWEI CLOUD EI Facial Recognition Service

8. Speech Processing Lab Guide (12%)

8.1 Speech Preprocessing

8.2 HUAWEI CLOUD EI Text-to-Speech Service

8.3 Speech Recognition Based on Seq2Seq

9. Natural Language Processing Lab Guide (10%)

9.1 HUAWEI CLOUD EI Natural Language Processing Service

9.2 Text Classification

9.3 Machine Translation

10. ModelArts Lab Guide (10%)

10.1 ExeML

10.2 Data Management

10.3 Built-in Algorithms for Deep Learning

10.4 Custom Basic Algorithms for Deep Learning

10.5 Custom Advanced Algorithms for Deep Learning

Share HCIP-AI-EI Developer V2.0 H13-321_V2.0 Free Dumps

1. Which of the following is NOT an acoustic feature of speech?

A. Amplitude

B. Semantic

C. Formant

D. Phase

Answer: B

2. With regard to taking selfies, which of the following is required to change an image from the front camera to a real scene image?

A. Translating

B. Vertical mirroring

C. Rotating

D. Horizontal mirroring

Answer: D

3. Which of the following methods CANNOT be used to label samples for object detection tasks in data management?

A. Enclosing the target with a circle

B. Enclosing the target with a rectangle

C. Enclosing the target with a polygon

D. Enclosing the target with an ellipse

Answer: D

4. What is the general workflow for ModelArts ExeML?

A. Service deployment -> Model training -> Data labeling

B. Data labeling -> Model training -> Service deployment

C. Model training -> Data labeling -> Service deployment

D. Data labeling -> Service deployment -> Model training

Answer: B

5. How can images be labeled for an image classification task?

A. Entering a category label for the image

B. Enclosing the target with an ellipse

C. Enclosing the target with a rectangle

D. Enclosing the target with a circle

Answer: A

6. Which of the following is NOT the limitation of TF-IDF?

A. Unable to retain sequence information

B. Not based on the distributional hypothesis

C. Curse of dimensionality

D. Unable to capture semantics

Answer: C

7. Which of the following is an ideal use case for convolutional neural networks, where they generally deliver good performance?

A. Computer vision

B. Speech recognition

C. Machine translation

D. Knowledge graph

Answer: A

8. Which of the following statements is false about the Gaussian distribution curve?

A. smaller variance indicates a taller and narrower curve.

B. The Gaussian curve is bell-shaped, with two ends low and the middle high.

C. larger average value indicates a taller and narrower curve.

D. The variance and average of the standard Gaussian distribution curve are 1 and 0, respectively.

Answer: C

9. Which of the following is one of the three layers of natural language processing (NLP)?

A. Phonological analysis

B. Resolution analysis

C. Lexical analysis

D. Semantic segmentation

Answer: C

10. Which of the following tasks can use the predictive analytics function of ModelArts ExeML?

A. Segmenting objects in images

B. Predicting weather and temperature changes

C. Identifying flower types

D. Detecting cats in images

Answer: B

11. Which of the following is NOT a step of data preprocessing for speech recognition?

A. Endpoint detection

B. Adding random noise

C. Removing duplicate audio with the same label

D. Pre-emphasis

Answer: C

12. In which of the following tasks can the Gaussians mixture model (GMM) be used? (Multiple choice)

A. Speech recognition

B. Voice noise reduction

C. Text-to-speech

D. Noise tracking

Answer: ABCD

13. Voice technology is one of the future development directions of Al. Which of the following are cutting-edge voice technologies? (Multiple choice)

A. Quantum computing

B. Language model

C. Neural network

D. Model adaptation technology

Answer: ABCD

14. What are the use cases of natural language processing (NLP)? (Multiple choice)

A. Automatic text summarization

B. Public opinion analysis

C. Q&A system

D. Text classification

Answer: ABCD

15. What are the typical challenges of speech recognition? (Multiple choice)

A. Recognition in high-noise scenarios

B. Recognition in multi-person scenarios

C. Dialect recognition

D. Far-field microphone recognition

Answer: ABCD

16. What are the typical challenges of named entity recognition (NER)? (Multiple choice)

A. Complex name nesting

B. The composition of named entities is complex.

C. Uncertain name length

D. There are numerous named entities of each type.

Answer: ABCD

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