HPE2-T38 Dumps: Path to Passing HPE AI and Machine Learning Exam

Passing HPE2-T38 exam is a required step for earning the HPE Product Certified - AI and Machine Learning certification, designed to validate your skills in designing and supporting solutions using HPE's AI and Machine Learning Development Environment. This certification empowers professionals to easily implement and train machine learning models, while removing complexities, optimizing costs, and accelerating innovation. By obtaining this certification, you demonstrate your proficiency in leveraging HPE's state-of-the-art tools and technologies to create robust AI and machine learning solutions. By mastering HPE's AI and Machine Learning Development Environment, certified professionals can drive innovation, accelerate project timelines, and deliver groundbreaking solutions that propel businesses forward in the digital age.

HPE2-T38 Exam Overview

Exam Type: Web-based 

Exam Duration: 1 hour 30 minutes 

Exam Length: 50 questions 

Passing Score: 70% 

Delivery Languages: English, Japanese, Korean

The HPE2-T38 exam is designed to evaluate your ability to work with HPE's machine learning solutions. It requires a thorough understanding of the HPE AI and Machine Learning Development Environment, enabling candidates to design, demonstrate, and support machine learning solutions effectively.

Who Should Take the HPE2-T38 Exam?

The ideal candidates for the HPE2-T38 exam are professionals involved in technical presales. These individuals should be able to design and demonstrate machine learning solutions and execute Proofs of Concept (POCs) across the machine learning stack. The HPE2-T38 exam is especially suitable for those who align relevant HPE machine learning solutions to customer goals and can clearly explain the benefits of proposed solutions to technical buyers.

Key Objectives Covered in HPE2-T38 Exam

The HPE2-T38 exam covers a wide range of topics to ensure candidates have comprehensive knowledge of the HPE AI and machine learning landscape. Below is a breakdown of the exam objectives:

Understand Machine Learning Ecosystem Fundamentals (13%)

Recognize the fundamentals of machine learning technology. Identify challenges customers face in training deep learning (DL) models. Classify potential components of a machine learning (ML) ecosystem.

Examine HPE Machine Learning Offerings (15%)

Recite key capabilities of HPE's AI-at-scale portfolio software. Align relevant HPE ML solutions to customer goals. Recognize different HPE deployment solutions.

Describe Requirements and Prerequisites for HPE ML Solutions (13%)

Compare HPE machine learning architecture and deployment options. Recognize common factors regarding required infrastructures.

Articulate the Business Value of HPE ML Solutions (24%)

Articulate the benefits of Machine Learning Development Management System (MLDMS). Articulate the benefits of Machine Learning Development Environment (MLDE). Describe how HPE AI offerings fit into the market.

Demonstrate and Explain How to Use HPE Machine Learning (ML) [PDK] (18%)

Explain the fundamentals of Product Development Kit (PDK). Demonstrate the ability to engage with data versioning and lineage. Explain how to train a new model. Explain how to deploy the model. Demonstrate the ability to automate and integrate these steps for deployment.

Compare HPE ML Enterprise Offerings to Open-Source Versions (7%)

Describe current enterprise features compared to open-source versions.

Engage with Customers (10%)

Qualify customers for HPE AI offerings. Identify the appropriate personas for engagement. Demonstrate a proof of concept (PoC).

Preparing for the HPE2-T38 Exam

To successfully pass the HPE2-T38 exam, candidates should be well-versed in HPE's AI and ML offerings, including both their technical aspects and business benefits. Focus on understanding the key capabilities of HPE's AI-at-scale software portfolio, the business value of HPE ML solutions, and how these solutions compare to open-source alternatives. Practical experience with HPE's machine learning tools, especially the Product Development Kit (PDK), is also crucial.

Tips for Success

Hands-on Practice: Gain practical experience with HPE's machine learning tools and solutions. Familiarity with using the PDK for model development and deployment is particularly valuable. 

Understand the Business Perspective: Besides technical skills, the exam also tests your ability to articulate the business value of HPE's solutions. Be prepared to explain how HPE's ML offerings can help organizations address specific challenges. 

Study Exam Objectives: Make sure you understand all the exam objectives thoroughly. Focus on areas where you feel less confident, especially topics like comparing enterprise offerings to open-source versions or articulating the benefits of MLDMS and MLDE. 

Exam Dumps: Take HPE2-T38 exam dumps to familiarize yourself with the question format and time constraints. This will also help you identify areas that need more study.

Share some HPE2-T38 exam dumps below.

1.Which feature of HPE machine learning PDK helps users to quickly iterate on model development?

A. Automated hyperparameter tuning

B. Real-time data monitoring

C. Code version control

D. Interactive visualization tools

Answer: A

2.What type of software is required to develop and deploy machine learning models with HPE solutions?

A. HPE Haven OnDemand

B. TensorFlow

C. Microsoft Excel

D. Jupyter Notebooks

Answer: B

3.Why is it important to consider the scalability and performance requirements before selecting HPE machine learning solutions?

A. To limit the types of machine learning algorithms that can be used

B. To increase the complexity of the models

C. To accommodate growing datasets and user demands

D. To minimize the cost of implementation

Answer: C

4.Which aspect of HPE machine learning PDK distinguishes it from open-source machine learning frameworks?

A. Seamless scalability capabilities

B. Built-in model explainability tools

C. Integration with popular IDEs

D. Compatibility with legacy systems

Answer: B

5.In the context of HPE machine learning, what is the purpose of the PDK?

A. Algorithm development

B. Data visualization

C. Machine learning model training

D. Predictive analytics

Answer: A

The HPE2-T38 exam is an excellent opportunity for professionals involved in technical presales to enhance their skills in designing and demonstrating HPE's AI and machine learning solutions. By understanding the fundamentals, aligning solutions to customer goals, and articulating the business value of HPE ML offerings, you can ensure a successful outcome in the exam. Focus on practical experience, thorough study of the exam objectives, and practice tests to increase your chances of success.