Overview
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
Sold by | Lumify Work (formerly known as DDLS) |
Categories | |
Fulfillment method | Professional Services |
Pricing Information
This service is priced based on the scope of your request. Please contact seller for pricing details.
Support
Please click continue on this listing to log your enquiry with your AWS account.
Alternatively, contact us by calling 1800 ULearn (853 276) or emailing training@lumifywork.com.
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