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 AWSÂ course
- Completed Deep Learning on AWSÂ course
Highlights
- Lumify Work is an official AWS Training Partner for the Australian, New Zealand and Philippines region. Through our Authorised AWS Instructors, we can provide you with a learning path that’s relevant to you and your organisation, so you can get more out of the cloud. We offer virtual and face-to-face classroom-based training to help you build your cloud skills and enable you to achieve industry-recognised AWS Certification.
- This course includes instructor-led training, presentations, demonstrations, practice labs, discussions, and a capstone project.
Details
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
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Alternatively, contact us by calling 1800 ULearn (853 276) or emailing  training@lumifywork.com .
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