AWS Cloud Practitioner 2023: ML, AI, & Data Analytics
|
Lower costs and gain deeper insights into data using AWS machine learning (ML) and artificial intelligence (AI) services. Explore Amazon SageMaker, Amazon Kinesis, Amazon Glue, and more.
About this course
Cloud customers can get deeper insights into their data while lowering costs with AWS machine learning (ML) and artificial intelligence (AI) services. AWS assists at every phase of the ML/AI adoption journey with the most comprehensive set of services, infrastructure, and implementation resources. Begin this course by discovering how ML and AI assist organizations like yours in generating growth and fixing challenging issues. Next, you will explore Amazon SageMaker, Amazon Lex, which is a fully managed AI service with cutting-edge natural language models, and Amazon Kendra, which can provide ML-powered instant answers and FAQs. Then you will focus on Amazon Athena, a serverless, interactive analytics solution, Amazon Kinesis, and Amazon Glue, a serverless data integration service. Finally, you will examine Amazon QuickSight and Amazon EMR, the industry-leading cloud big data solution for petabyte-scale data processing, interactive analytics, and ML. This course is one of a collection that prepares learners for the AWS Certified Cloud Practitioner (CLF-C02) exam.
Learning objectives
Discover the key concepts covered in this course
Define machine learning and artificial intelligence
Compare amazon sagemaker, lex, and kendra
Show all
User Reviews
Be the first to review “AWS Cloud Practitioner 2023: ML, AI, & Data Analytics”
Related Products
Google Cloud Fundamentals
Gain foundational knowledge of Google Cloud services, architecture, and best practices for cloud deployment.
Cloud Computing for Business Leaders
Understand the business impact of cloud computing and how to leverage it for organizational success.
Cloud for Modern Business
Explore how cloud computing is transforming modern business practices and enabling innovation.
Monolith to Microservices at Scale
Learn how to transition from monolithic architectures to microservices for better scalability and maintainability.
Cloud Native Application Architecture
Understand cloud-native application design principles, including microservices and containerization.
Design for Availability, Reliability, and Resiliency
Learn design principles to ensure cloud applications are highly available, reliable, and resilient to failures.
There are no reviews yet.