HCIA-AI V3.5 Certification
victoriameiselThe H13-311_V3.5 exam is the latest and most updated version for the HCIA-AI V3.5 Certification. This certification is essential for those looking to advance their career in the field of artificial intelligence. Passcert has newly released comprehensive HCIA-AI V3.5 Certification H13-311_V3.5 Dumps that will allow you to prepare for the exam in a more thorough and effective way. These HCIA-AI V3.5 Certification H13-311_V3.5 Dumps include detailed questions and answers, practice tests, and study guides that cover all the key topics and concepts. If you are diligently going through all of our HCIA-AI V3.5 Certification H13-311_V3.5 Dumps, then you will be well-equipped and confident to clear the H13-311_V3.5 exam on the first attempt, ensuring your success and paving the way for future opportunities in the AI field.
Passing the HCIA-AI V3.5 certification will indicate that you: (1) Understand the AI development history, Huawei Ascend AI system, Huawei full-stack all-scenario AI strategy, cutting-edge AI applications, and algorithms related to traditional machine learning and deep learning (2) Be able to build, train, and deploy neural networks by using the MindSpore development framework (3) Be ready to take on AI positions in sales, marketing, product management, project management, technical support, and more
Target Audience
Personnel who hope to become AI engineers
Personnel who hope to obtain an HCIA-AI certificate
Personnel who hope to know how to use, manage, and maintain Huawei AI products and AI services
Prerequisites
Possess the basic knowledge of advanced mathematics, and have studied the pre-course of "Math Basics".
Familiar with Python language, and have studied the pre-course of "Python Basics".
Huawei HCIA-AI V3.5 Certification Exam Overview
| Exam Code | H13-311 |
| Exam Name | HCIA-AI |
| Exam Language | ENU/CHS |
| Question Type | Single Answer, Multiple Answer, True-false Question, Fill in the blank answers, Drag and drop item |
| Exam Fees | 200 USD |
| Exam Duration | 90 min |
| Passing Score | 600 / 1000 |
Key Points Percentage
| Key Points | Percentage |
| AI Overview | 15% |
| Machine Learning Overview | 20% |
| Deep Learning Overview | 25% |
| AI Development Framework | 20% |
| Introduction to Huawei AI Platforms | 14% |
| Cutting-edge AI applications | 6% |
AI Overview
AI Overview
Application Fields of AI
Huawei's AI Development Strategy
Controversies Over AI and Its Future
Machine Learning Overview
Machine Learning Algorithms
Types of Machine Learning
Machine Learning Process
Important Machine Learning Concepts
Common Machine Learning Algorithms
Deep Learning Overview
Deep Learning
Training Rules
Activation Functions
Normalization
Optimizers
Neural Network Types
AI Development Framework
AI Framework Development
MindSpore
MindSpore Features
MindSpore Development Components
AI Application Development Process
Introduction to Huawei AI Platforms
Huawei Ascend Computing Platform
Huawei Cloud EI Platform
Huawei Device AI Platforms
Cutting-edge AI applications
Reinforcement Learning
GAN
Knowledge Graph
Intelligent Driving
Quantum Computing and Machine Learning
Share HCIA-AI V3.5 Certification H13-311_V3.5 Free Dumps
1. Which of the following technologies is commonly used for image feature extraction and related research?
A. Convolutional neural network
B. Naive Bayes classification algorithm
C. Long short-term memory (LSTM) network
D. Word2Vec
Answer: A
2. "Batch inference is a batch job that performs inference on batch data. There is no need for model training before using batch inference." Which of the following is true about this statement?
A. This statement is correct. With batch inference, training is no longer required.
B. This statement is correct. Inference means the end of training.
C. This statement is incorrect. Model training is required before inference is performed.
D. This statement is incorrect. No training is required before batch inference.
Answer: C
3. Consider a scenario where a machine learning algorithm is used to filter spam. According to the definition of machine learning, which of the following describes the experience E?
A. Spam filtering
B. Accuracy of spam filtering
C. All tagged spam and genuine emails in the past three years
D. Email addresses
Answer: C
4. A computer uses labeled images to learn and determine which images contain apples and which contain pears. Which of the following types of machine learning is most applicable to this scenario?
A. Supervised learning
B. Unsupervised learning
C. Semi-supervised learning
D. Reinforcement learning
Answer: A
5. Which of the following statements is true about classification models and regression models in machine learning?
A. For regression problems, the output variables are discrete values. For classification problems, the output variables are continuous values.
B. The most commonly used indicators for evaluating regression and classification problems are accuracy and recall rate.
C. There may be overfitting in both regression and classification problems.
D. Logistic regression is a typical regression model.
Answer: C
6. During neural network training, which of the following values is continuously updated by using the gradient descent method to minimize the loss function?
A. Hyperparameter
B. Feature
C. Number of samples
D. Parameter
Answer: D
7. Which of the following points constitute a support vector of the SVM algorithm without considering regularization terms?
A. Points on the separating hyperplane
B. Farthest points from the separating hyperplane
C. Points closest to the separating hyperplane
D. Points of a certain type
Answer: C
8. Which of the following are false about convolutional neural networks?
A. A convolutional neural network may contain convolutional, pooling, and fully connected layers.
B. Convolution kernels cannot extract global features of images.
C. Common pooling includes max pooling and average pooling.
D. When an image is processed, convolution is implemented by using a scanning window.
Answer: B
9. Overfitting problems can be avoided through dataset expansion. Which of the following statements is true about dataset expansion?
A. The larger the dataset, the lower the probability of overfitting.
B. The larger the dataset, the higher the probability of overfitting.
C. The smaller the dataset, the lower the probability of overfitting.
D. The probability of overfitting decreases when the dataset increases or decreases.
Answer: A
10. Which of the following is NOT a complexity feature of Al computing?
A. Mixed precision computing
B. Parallel data and computing
C. Parallel communication and computing
D. Parallel processing of structured and unstructured data
Answer: D
11. Which of the following statements about the running process of the MindArmour subsystem is false?
A. Configuration policies: Define test policies based on threat vectors and trustworthiness certification requirements and select appropriate test data generation methods.
B. Fuzzing execution: Generate trusted test data randomly based on the model coverage and configuration policies.
C. Evaluation report: Generate, an evaluation report based on built-in or user-defined trustworthiness metrics.
D. Trustworthiness enhancement: Use preset methods to enhance the trustworthiness of Al models.
Answer: B
12. Which of the following are topics of speech processing research?
A. Speech recognition
B. Voice processing
C. Speech wake-up
D. Voiceprint recognition
Answer: ABCD
Related Courses and Certification
Also Online IT Certification Courses & Online Technical Certificate Programs
SIIT is on a mission to make technology education and professional training more accessible, so more people can show off their talents and take their tech careers to the next level. All courses are tailored to meet individual specific career needs, leading to Tech Skills Acquisition and Professional Certification.
Jobs Vacancy
The Jobs portal provides you with real time Jobs Opening and Vacancy Updates curated globally. Start applying for your dream job with ease in any location you choose.
Learn More >>
CV Builder
The CV Builder provides you with comprehensive guide and proven steps to take in writing a professional CV including top CV templates to get you started quickly.
Learn More >>
