HPE AI and Machine Learning (0001205272)
Learn how to use HPE Machine Learning Data Management and HPE Machine Learning Development Environment. Hands-on labs and activities will guide you through machine learning and deep learning fundamentals and is the preparation for the HPE2-T38 exam.
Prepares for this certification
HPE Product Certified – AI and Machine Learning
Description
This course teaches you how to use HPE Machine Learning Data Management and HPE Machine Learning Development Environment. Hands-on labs and activities will guide you through machine learning and deep learning fundamentals. You will learn about the architecture and ways to deploy HPE machine learning solutions. You will also explore HPE Machine Learning Data Management repos and pipelines.
Objectives
This course teaches you:
- How to run deep learning experiments and train models using the HPE Machine Learning Development Environment.
- The HPE Machine Learning Development System, a solution that combines HPE Machine Learning Development Environment software and HPE infrastructure.
- How to position the HPE Machine Learning Development solutions based on customer needs and how to set up a proof of concept or demo environment.
Target audience
The ideal candidates for this exam are involved in technical presales, including those who can design and demonstrate machine learning solutions, and execute POCs, across the Machine Learning stack. The candidates can align relevant HPE Machine Learning solutions to customer goals and explain the unique benefits of a proposed solution in a way that the technical buyer can understand. This course prepares you for the HPE2-T38 – HPE AI and Machine Learning exam.
List of subjects
- Understand Machine Learning and Deep Learning Fundamentals
- Machine learning technology evolution
- Machine learning and deep learning model training
- Consideration of issues data scientists confront during model training
- Standard tools and frameworks for deep learning pipelines such as PyTorch and TensorFlow
- Hyperparameter optimization (HPO)
- Distributed (multi-GPU) training
- Describe HPE Machine Learning Solutions’ Value Proposition
- HPE Machine Learning Data Management value proposition
- HPE Machine Learning Development Environment value proposition
- Common customer challenges in deep learning
- A high-level look at how HPE Machine Learning Data Management and HPE Machine Learning
- Development Environment address these challenges
- Where HPE machine learning solutions fits in the market
- A high-level look at HPE Machine Learning Data Management and HPE Machine Learning Environment capabilities
- Distinguishing features of HPE Machine Learning Development Systems
- Using HPE Machine Learning Data Management Capabilities
- Repos and their data versioning and data lineage capabilities
- Pipelines and ways to use them
- Using HPE Machine Learning Development Environment to Train Models
- HPE Machine Learning Development Environment software architecture
- Flexible options for software-only deployment on on-prem servers or in the cloud
- Intro to training a model on the HPE Machine Learning Development Environment
- Detailed AI and Machine Learning training concepts
- Using HPE Machine Learning Development Environment to run experiments, including experiments that feature distributed training and HPO
- Experiment concepts and the relationships between workloads, trials, and experiments
- Scheduling concepts
- Model registry
- Qualifying Customers and Running a Demonstration
- Engaging and qualifying customers for an HPE Machine Learning Development Environment opportunity
- Engaging and qualifying customers for an HPE Machine Learning Development System opportunity
- Running a demonstration
The price for this course excludes any costs for taking an exam. If an exam voucher is taken after the training, an additional invoice will be sent.
