Artificial Intelligence and Machine Learning with AWS
Overview
Artificial Intelligence and Machine Learning with AWS is designed to prepare attendees to use AWS cloud service for production AI and machine learning solutions.
Day 1 covers core cloud services and basic hosted AWS AI/ML elements such as Sage Maker and Bedrock. Day 2 explores AWS prescriptive AI/ML application architectures, data storage and pipelines as well as training and inference approaches. Each module is divided evenly between lecture/discussion and hands on lab work, giving attendees practical experience with the cloud services in question.
Day 3 covers a host of additional important topics, including observability, security, scaling and various related AWS hardware features, such as GPU and Inferentia.
Upon completion attendees will have experience working with AWS AI/ML services and building complete AI/ML solutions in the cloud.
Duration
3 Days
Who Should Take This Course
Audience
Data Scientists, Data Engineers, AI and Machine Learning Engineers, AIMLOps professionals.
Prerequisites
Participants should have some familiarity with AI and machine learning.
Why You Should Take This Course
- Be able to design and operation sophisticated production grade ML/AI solutions on AWS
- Understand AWS machine learning and artificial intelligence tools
- Gain familiarity with AWS ML and AI core service offerings
- Work with common AWS AI/ML use patterns and architectures
- Understand AWS design and deployment options for AI & ML pipelines
- Learn about AWS AI/ML observability and security features
- Understand AWS AI/ML scaling options and costs