Updated: Sep 04, 2026
No. of Questions: 108 Questions & Answers with Testing Engine
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| Certification Vendor: | Hewlett Packard Enterprise (HPE) |
|---|---|
| Exam Name: | HPE AI and Machine Learning |
| Exam Number: | HPE2-T38 |
| Exam Duration: | 90 minutes |
| Real Exam Qty: | 50 |
| Passing Score: | 70% |
| Exam Format: | Drag and drop, Fill in the blank, Multiple choice |
| Certificate Validity Period: | 3 years |
| Available Languages: | Korean, Japanese, English |
| Exam Price: | $75 - $140 USD |
| Recommended Training: | HPE AI and Machine Learning Training Course |
| Exam Registration: | Pearson VUE Registration |
| Sample Questions: | HP HPE2-T38 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; recommended knowledge of AI/ML concepts and HPE solutions |
| Official Syllabus URL: | https://www.hpe.com/us/en/certification/exams/hpe2-t38.html |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: HPE vs Open Source Machine Learning Solutions | 7% | - Feature comparison - Enterprise readiness and support - Scalability and performance differences |
| Topic 2: Using HPE Machine Learning Professional Development Kit (PDK) | 18% | - Model training and optimization - Automation and integration workflows - Data versioning and lineage management - PDK fundamentals and architecture - Model deployment and monitoring |
| Topic 3: Business Value of HPE Machine Learning Solutions | 24% | - Cost optimization and efficiency benefits - Differentiators compared to alternative solutions - Accelerated innovation and time-to-value |
| Topic 4: Machine Learning Ecosystem Fundamentals | 13% | - Challenges in training deep learning models - Basics of machine learning technology - Components of a machine learning ecosystem |
| Topic 5: HPE Machine Learning Offerings | 15% | - Different deployment models for HPE solutions - Capabilities of HPE AI at-scale portfolio software - Aligning HPE solutions with customer requirements |
| Topic 6: Requirements and Prerequisites for HPE Machine Learning Solutions | 13% | - Hardware and software requirements - Infrastructure and environment prerequisites |
Question 1
What does the HPE Ezmeral Unified Analytics Software primarily offer?
Response:
A. Managed, secure enterprise-grade open-source frameworks
B. Hardware optimization for ML models
C. Data encryption services
D. Basic data processing tools
Question 2
HPE ProLiant Servers are optimized for:
Response:
A. Computer vision inference and natural language processing
B. Database management
C. Web hosting services
D. E-commerce platforms
Question 3
How do HPE ML solutions contribute to a business''s scalability?
Response:
A. By limiting the business to current operations
B. By offering scalable solutions that grow with the business
C. By focusing solely on short-term goals
D. By increasing operational costs disproportionately
Question 4
When it comes to data privacy compliance, how do HPE solutions compare to open-source?
Response:
A. Neither addresses data privacy compliance
B. Both are equally effective in compliance
C. Open-source versions are better at ensuring compliance
D. HPE solutions often have more robust compliance mechanisms
Question 5
What does ''ensemble learning'' refer to in ML?
Response:
A. Learning from a single model
B. A method for data preprocessing
C. Training models sequentially
D. Combining predictions from multiple models
Solutions:
| Question 1 Answer: A | Question 2 Answer: A | Question 3 Answer: B | Question 4 Answer: D | Question 5 Answer: D |
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