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| Certification Vendor: | Hewlett Packard Enterprise |
| Exam Name: | HPE AI and Machine Learning (HPE2-T38) |
| Exam Number: | HPE2-T38 |
| Available Languages: | English |
| Related Certifications: | HPE Sales Certification HPE Technical Certifications (AI/Data/Hybrid Cloud tracks) |
| Exam Format: | Multiple choice |
| Recommended Training: | HPE AI and Machine Learning Training Resources |
| Exam Registration: | HPE Certification Portal |
| Sample Questions: | HP HPE2-T38 Sample Questions |
| Exam Way: | Online proctored or onsite testing depending on region and provider availability |
| Official Syllabus URL: | https://certification.hpe.com |
| Section | Objectives |
|---|---|
| Topic 1: Artificial Intelligence Fundamentals | - Types of machine learning (supervised, unsupervised, reinforcement learning) - Core AI concepts and terminology - AI use cases in enterprise environments |
| Topic 2: MLOps and Operationalization | - Model lifecycle management - Monitoring and governance of ML systems - Automation and CI/CD for ML |
| Topic 3: HPE AI and Machine Learning Solutions | - HPE GreenLake for AI workloads - Hybrid cloud AI infrastructure concepts - HPE Ezmeral for ML operations |
| Topic 4: Data Engineering for AI | - Data preprocessing and feature engineering - Data pipelines and storage considerations |
| Topic 5: Machine Learning Lifecycle | - Model deployment and monitoring - Data collection and preparation - Model training, validation, and evaluation |
1. Adequate data storage is necessary for machine learning. This storage should be:
Response:
A) Limited to cloud storage only
B) Restricted to local storage only
C) Scalable to handle large datasets
D) Minimal, as ML models require little data
2. What is the primary goal of customer engagement?
Response:
A) To reduce marketing costs
B) To increase product prices
C) To maximize short-term sales
D) To build long-term customer relationships
3. What role does ''data normalization'' play in ML?
Response:
A) Enhancing model security
B) Improving algorithm performance
C) Reducing data storage needs
D) Simplifying the programming process
4. When it comes to data privacy compliance, how do HPE solutions compare to open-source?
Response:
A) HPE solutions often have more robust compliance mechanisms
B) Neither addresses data privacy compliance
C) Both are equally effective in compliance
D) Open-source versions are better at ensuring compliance
5. For machine learning solutions, which of these operating systems is typically preferred?
Response:
A) An OS without multitasking capabilities
B) DOS
C) Any modern OS capable of supporting ML frameworks
D) Windows 95
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: C |
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