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The HPE AI and Machine Learning HPE2-T38 certification validates your ability to design and support AI solutions using the HPE Machine Learning Development Environment (MLDE). This exam focuses on optimizing workflows, cutting operational costs, and enabling businesses to deploy ML models without unnecessary complexity, making it crucial for professionals involved in AI innovation.
This certification is ideal for professionals in technical presales roles, those designing and demonstrating machine learning solutions, and individuals running Proof of Concept (PoC) projects. If you are responsible for aligning machine learning solutions with customer goals and explaining technical benefits in an understandable way, this exam is tailored for you.
Exam ID: HPE2-T38
Type: Web-based
Duration: 1 hour 30 minutes
Questions: 50
Passing Score: 70%
Languages: English, Japanese, Korean
The exam covers several key areas to assess your expertise in HPE’s machine learning offerings. Each topic is weighted differently, requiring a strategic study approach.
To succeed, candidates need a solid understanding of the ML ecosystem, including:
● Recognize the fundamentals of the technology.
● Identify the challenges customers face in training DL models.
● Classify Potential Components of an ML ecosystem.
You’ll need to understand HPE’s AI-at-scale portfolio and align its solutions to business goals. Key topics include:
● Recite key capabilities of HPEs AI at-scale portfolio software
● Align relevant HPE ML solutions to customer goals
● Recognize different HPE deployment solutions
Candidates should be familiar with:
● Compare HPE machine learning (ML) architecture and deployment options.
● Recognize some common factors regarding required infrastructures.
The ability to explain the business benefits of HPE’s tools is a crucial part of the exam. This includes:
● Articulate the benefits of MLDMS
● Articulate the benefits of MLDE
● Describe how HPE AI offerings fit in the market
The PDK (Performance Development Kit) is a vital tool for hands-on work. You must demonstrate your ability to:
● Explain the fundamentals of PDK
● Demonstrate an ability to engage with data versioning and lineage
● Explain how to train a new model
● Explain how to deploy the model
● Demonstrate ability to automate and integrate these steps for deployment
HPE’s enterprise offerings provide several advantages over open-source solutions. In this section, candidates must:
● Describe Current Enterprise features
Building strong customer relationships is a critical skill for certification holders. You should be able to:
● Qualify customers for HPE AI offerings
● Identify the appropriate personas for engagement
● Demonstrate a proof of concept (PoC)
1.Which aspect of HPE’s machine learning solutions can help businesses in developing a better understanding of customer needs and preferences?
A. Integration with CRM systems
B. Algorithm transparency
C. Automated model training
D. Real-time data processing
Answer: A
2.What are some of the current enterprise features offered by HPE in their machine learning solutions?
A. Automated machine learning model training
B. Real-time monitoring and predictive maintenance features
C. Integration with existing IT infrastructure
D. Advanced analytics capabilities
Answer: C
3. What deployment options are available for models created using the HPE Machine Learning [PDK]?
A. Cloud deployment only
B. Hybrid deployment (on-premises and cloud)
C. On-premises deployment only
D. No deployment options are available
Answer: B
4. What is a key prerequisite for implementing HPE machine learning solutions?
A. Understanding of data pre-processing techniques
B. Experience in neural networks
C. Basic knowledge of Python programming language
D. High-speed internet connection
Answer: C
5. What is an essential requirement for ensuring model interpretability in HPE machine learning solutions?
A. Explainable AI techniques
B. Biometric authentication
C. Real-time prediction capabilities
D. Black-box algorithms
Answer: A
6. What is a key feature of the HPE Machine Learning [PDK] for model training?
A. Real-time data visualization
B. Email notifications for model status
C. Automated hyperparameter tuning
D. Cloud-based data storage
Answer: C
7. What is a benefit of using HPE Machine Learning enterprise offerings instead of open-source versions for businesses?
A. Higher level of community involvement
B. Lower initial investment
C. Less control over customization
D. Improved compatibility with existing systems
Answer: D
8. What is data preprocessing in machine learning?
A. It refers to the transformation of raw data into a proper format for analysis
B. It is the process of selecting the most relevant features for the model
C. It involves removing or correcting errors in the data
D. It is the final step in the machine learning process
Answer: A
9. What role can HPE Machine Learning solutions play in supply chain management?
A. Decreasing supplier collaboration
B. Increasing inventory levels
C. Enhancing demand forecasting accuracy
D. Delaying order fulfillment
Answer: C
10. How can HPE ML solutions enhance cybersecurity measures for organizations?
A. Reducing the need for security protocols
B. Increasing vulnerability to cyber attacks
C. Detecting and mitigating threats in real-time
D. Improving physical security measures
Answer: C
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