Amazon SageMaker Studio for Data Scientists
Prepare, build, train, deploy, and monitor machine learning (ML) models with AWS SageMaker.
Amazon SageMaker Studio helps data scientists rapidly prepare, build, train, deploy, and monitor machine learning (ML) models.
To do this, it brings together a wide range of features specifically designed for machine learning.
This advanced-level training prepares experienced data scientists to use the tools integrated into SageMaker Studio—including the Amazon CodeWhisperer and Amazon CodeGuru Security Scan extensions—to improve productivity at every stage of the machine learning lifecycle.
This course includes presentations, hands-on exercises, demonstrations, discussions between participants and the instructor, and a capstone project.
- Course level: Advanced
- Duration: 3 days
Updated June 2026
Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
7 courses found
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- Delivery Format: Virtual Learning
- Date 06-08 January, 2027 | 9:00 AM to 5:00 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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- Delivery Format: Virtual Learning
- Date 29-31 March, 2027 | 9:00 AM to 5:00 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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- Delivery Format: Virtual Learning
- Date 07-09 April, 2027 | 8:30 AM to 4:30 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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- Delivery Format: Virtual Learning
- Date 14-16 July, 2027 | 9:00 AM to 5:00 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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- Delivery Format: Virtual Learning
- Date 02-04 August, 2027 | 9:00 AM to 5:00 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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- Delivery Format: Virtual Learning
- Date 06-08 October, 2027 | 9:00 AM to 5:00 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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- Delivery Format: Virtual Learning
- Date 08-10 November, 2027 | 9:00 AM to 5:00 PM
- Location: Virtual (Eastern Standard Time)
- Language: English
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