No confidence for the exam? The HP Using HPE Cray AI Development Environment VCE test engine is your best select: 42 practice questions for the HPE2-N69 exam at Test4Engine.
HP HPE2-N69 Exam Overview:
| Certification Vendor: | Hewlett Packard Enterprise (HPE) |
|---|---|
| Exam Name: | Using HPE Cray AI Development Environment |
| Exam Number: | HPE2-N69 |
| Exam Duration: | 90 minutes |
| Exam Format: | Multiple Choice, Scenario-based, Drag & Drop, Multiple Response |
| Related Certifications: | HPE AI and Machine Learning [2022] |
| Exam Price: | $200 USD |
| Available Languages: | Japanese, Korean, English |
| Passing Score: | 70% - 75% |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 40 - 60 |
| Recommended Training: | Using HPE Cray AI Development Environment (Rev. 22.21) |
| Exam Registration: | HPE Certification Portal Pearson VUE Registration |
| Sample Questions: |  |
| Exam Way: | Online proctored or at authorized Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; recommended: basic AI/ML knowledge, 3–6 months hands-on experience with HPE or similar ML platforms |
| Official Syllabus URL: | https://certification-learning.hpe.com |
HP HPE2-N69 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: ML and DL Fundamentals & Customer Challenges | 24% | - Explain core machine learning and deep learning concepts - Identify common challenges in training deep learning models - Articulate business value and use cases for HPE solutions |
| Topic 2: Environment Usage & Workload Management | 33% | - Navigate web UI and CLI tools - Run and manage different types of experiments - Understand resource allocation and scheduling |
| Topic 3: Integration and Operations | 13% | - Monitor cluster health and performance - Manage data and model lifecycle |
| Topic 4: Architecture and Deployment | 15% | - Explain deployment options and system components - Differentiate from open-source Determined AI - Describe software architecture of HPE Cray AI/ML Environment |
| Topic 5: Solution Qualification & Sizing | 15% | - Qualify customers for HPE ML solutions - Perform basic sizing and configuration - Position against market alternatives |
HPE2-N69 Exam FAQ — Clear the Nerves
The HP Using HPE Cray AI Development Environment is HP's certification exam for HPE Product Certified - AI and Machine Learning, at the Specialist level. It's demanding enough to intimidate — timed practice is the cure. Related credentials include HPE AI and Machine Learning [2022].
Yes:
After any course, build confidence with the 42 practice questions for the HP Using HPE Cray AI Development Environment — every answer expert-verified.
Through the vendor's official registration channels:
The HP Using HPE Cray AI Development Environment is delivered Online proctored or at authorized Pearson VUE test centers — pick the arrangement that suits you when booking.
90 minutes for 40 - 60 questions. The Test4Engine APP engine imitates the real test — set timed exams, mark performance, point out mistakes — so exam day feels rehearsed.
The HP Using HPE Cray AI Development Environment blueprint spans 5 domains — including Solution Qualification & Sizing (15%), Architecture and Deployment (15%), ML and DL Fundamentals & Customer Challenges (24%). The complete outline above lists every subtopic; our IT staff keep the material aligned daily.
No mandatory prerequisites; recommended: basic AI/ML knowledge, 3–6 months hands-on experience with HPE or similar ML platforms Eligibility rules change over time, so verify the current requirements on the official page (official HPE2-N69 exam page) before registering.
$200 USD per attempt, 70% - 75% to pass. Retakes cost the full fee — practice whenever you want with the 42 practice questions for the HPE2-N69 exam at Test4Engine.
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HP Using HPE Cray AI Development Environment Sample Questions:
An HPE Machine Learning Development Environment resource pool uses priority scheduling with preemption disabled. Currently Experiment 1 Trial I is using 32 of the pool's 40 total slots; it has priority 42. Users then run two more experiments:
* Experiment 2:1 trial (Trial 2) that needs 24 slots; priority 50
* Experiment 3; l trial (Trial 3) that needs 24 slots; priority I
What happens?
- A. Trial I is allowed to finish. Then Trial 3 is scheduled.
- B. Trial 1 is allowed to finish. Then Trial 2 is scheduled.
- C. Trial 3 is scheduled on 8 of the slots. Then, after Trial 1 has finished, it receives 16 more slots.
- D. Trial 2 is scheduled on 8 of the slots. Then, alter Trial 1 has finished, it receives 16 more slots.
Correct Answer: C 🗳️
Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).
ML engineers are defining a convolutional neural network (CNN) model bur they are not sure how many filters to use in each convolutional layer. What can help them address this concern?
- A. Using a variable learning late
- B. Using hyperparameter optimization (HPO)
- C. Distributing the training across multiple CPUs
- D. Training the model on multiple epochs
Correct Answer: B 🗳️
Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).
A company has an HPE Machine Learning Development Environment cluster. The ML engineers store training and validation data sets in Google Cloud Storage (GCS). What is an advantage of streaming the data during a trial, as opposed to downloading the data?
- A. Setting up streaming is easier that setting up downloading.
- B. The trial can better separate training and validation data.
- C. The trial can more quickly start up and begin training the model.
- D. Streaming requires just one bucket, while downloading requires many.
Correct Answer: C 🗳️
Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).
You are helping a customer start to implement hyper parameter optimization (HPO) with HPE Machine learning Development Environment. An ML engineer is putting together an experiment config file with the desired Adaptive A5HA settings. The engineer asks you questions, such as how many trials will be trained on the max length and what the min length for all trials will be.
What should you explain?
- A. The engineer should run a preliminary experiment with one tenth the desired number of max trials, assess the results, and then run the full experiment.
- B. The engineer should access the HPE Machine Learning Development online calculator and input the mode, max_trials, max_length, divisor, and max_runs.
- C. The engineer should run the "det preview-search" command, referencing the experiment config.
- D. The engineer should upload the experiment config to the HPE Machine Learning Development Environment WebUl and view the graph of the experiment plan.
Correct Answer: B 🗳️
Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).
A trial is running on a GPU slot within a resource pool on HPE Machine Learning Development Environment. That GPU fails. What happens next?
- A. The trial fails, and the ML engineer must manually restart it from the latest checkpoint using the WebUI.
- B. The trial tails, and the ML engineer must restart it manually by re-running the experiment.
- C. The conductor reschedules the trial on another available GPU in the pool, and the trial restarts from the latest checkpoint.
- D. The concluded reschedules the trial on another available GPU in the pool, and the trial restarts from the state of the latest training workload.
Correct Answer: C 🗳️
Explanation: Only visible for Test4Engine members. You can sign-up / login (it's free).
