Overview
Learn to use Amazon SageMaker Studio to boost productivity at every step of the ML lifecycle.
Amazon SageMaker Studio helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. This course prepares experienced data scientists to use the tools that are part of SageMaker Studio to improve productivity at every step of the ML lifecycle.
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Skills Covered
In this course, you will learn to:
- Accelerate the preparation, building, training, deployment, and monitoring of ML solutions by using Amazon SageMaker Studio.
Who Should Attend
This course is intended for:
- Experienced data scientists who are proficient in ML and deep learning fundamentals. Relevant experience includes using ML frameworks, Python programming, and the process of building training, tuning, and deploying models.
Course Curriculum
Prerequisites
We recommend that all students complete the following AWS course prior to attending this course:
We recommend students who are not experienced data scientists complete the following two courses followed by 1-year on-the-job experience building models prior to taking this course:
Course Modules
Exam & Certification
This course is not associated with any certification.