This three-day, advanced level 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.

Duration: 3 Days

What you'll learn:

• Accelerate the preparation, building, training, deployment, and monitoring of ML solutions by using Amazon SageMaker Studio

Course Subjects:

• Amazon SageMaker Setup and Navigation
• Data Processing
• Model Development
• Deployment and Inference
• Monitoring
• Managing SageMaker Studio Resources and Update
• Capstone Lab

Target Audience:

• 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

Prerequisites:

It is recommended that all attendees have the following prior to attending this course:

• Completed AWS Technical Essentials course
• Experience in Python programming

It is recommended that attendees who are not experienced data scientists also have the following prior to attending this course:

• Completed The Machine Learning Pipeline on AWS course
• Completed Deep Learning on AWS course