HP HPE2-N69 Exam Details & Actual Exam Questions

  • Exam Code/Number: HPE2-N69
  • Exam Name/Title: Using HPE Cray AI Development Environment
  • Certification Provider: HP
  • Corresponding Certification: HPE Product Certified - AI and Machine Learning
  • Exam Questions: 42
  • Updated On: Jul,22 2026
  • Certification Level: Foundational

HP Using HPE Cray AI Development Environment Exam Questions

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HP HPE2-N69 Exam Overview:

Certification Vendor:Hewlett Packard Enterprise (HPE)
Exam Name:Using HPE AI and Machine Learning
Exam Number:HPE2-N69
Real Exam Qty:40
Available Languages:English, Japanese, Korean
Exam Duration:90 minutes
Related Certifications:HPE Machine Learning Development Environment
HPE AI and Machine Learning Certification Track
Exam Format:Multiple choice
Passing Score:65%
Recommended Training:HPE AI and Machine Learning Training (Official)
Exam Registration:HPE Certification Portal
Pearson VUE HPE Exams
Sample Questions:HP HPE2-N69 Sample Questions
Exam Way:Online proctored or Pearson VUE test center
Pre Condition:No strict prerequisites (recommended basic ML and Linux/Python familiarity)
Official Syllabus URL:https://certification-learning.hpe.com/tr/exams

HP HPE2-N69 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Machine Learning and Deep Learning Fundamentals24%- Core ML concepts
  • 1. Neural networks and deep learning basics
    • 2. Supervised and unsupervised learning
      Topic 2: Using HPE Machine Learning Development Environment33%- Experiment lifecycle
      • 1. Model training and configuration
        • 2. Experiment scheduling and resource allocation
          • 3. Hyperparameter optimization (HPO)
            Topic 3: Business Value of HPE ML Solutions13%- Use cases and industry applications
            • 1. AI/ML in enterprise environments
              • 2. Value proposition of HPE ML platform
                Topic 4: Customer Engagement and Solution Design15%- Solution positioning
                • 1. Customer requirements analysis
                  • 2. ML deployment considerations
                    Topic 5: Architecture of HPE Machine Learning Development Environment15%- System architecture
                    • 1. Distributed training environment
                      • 2. Resource pools and scheduling


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