Amazon SageMaker Studio helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models quickly. It does this by bringing together a broad set of capabilities purpose-built for ML. This course prepares experienced data scientists to use the tools that are a part of SageMaker Studio, including Amazon CodeWhisperer and Amazon CodeGuru Security scan extensions, to improve productivity at every step of the ML lifecycle.
Prerequisites
We recommend that all attendees of this course have:
• Experience using ML frameworks
• Python programming experience
• At least 1 year of experience as a data scientist responsible for training, tuning, and
deploying models
• AWS Technical Essentials digital or classroom training
THIS COURSE IS NOT ELIGIBLE FOR TRAINING BUNDLES.
Purpose
| For data scientists who want to prepare, build, train, deploy, and monitor machine learning (ML) models quickly. |
Audience
| Experienced data scientists who are proficient in ML and deep learning fundamentals |
Role
| Data Scientists |
Skill level
| Advanced |
Style
| Presentations | Hands-on Labs | Demonstrations |Discussions | Capstone |
Duration
| 3 days |
Related technologies
| AWS Cloud |
Course objectives
- Accelerate the process to prepare, build, train, deploy, and monitor ML solutions using Amazon SageMaker Studio