You will learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. Real life use case includes customer retention analysis to inform customer loyalty programs.
This course is for individuals who seek an understanding of how to manage, optimize, and predict costs as you run workloads on AWS. You learn how to implement architectural best practices, explore cost optimization strategies, and design patterns to help you architect ...
In this course, you will learn best practices for designing and using cloud-based video workflows. It covers important concepts related to video processing and delivery, the variables that can impact migration decisions, and real-world examples of hybrid and cloud use cases for ...
DevOps Engineering on AWS teaches you how to use the combination of tools, practices, and cultural philosophy of DevOps to improve an organization’s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers Continuous ...
In this course, you will learn how to efficiently use AWS security services for optimal security and compliancy in the AWS cloud. This course focuses on the AWS-recommended best practices that you can implement to enhance the security of your data and systems in the cloud. The ...