What is Practical Data Science with Amazon SageMaker training and is it worth it?
This one-day course teaches you how to apply data science techniques using Amazon SageMaker. You’ll complete the full machine learning workflow—from data prep and visualization to training, tuning, and deployment. It’s a fast, practical way to get real-world experience with AWS ML tools.
Will this training course help me build and deploy ML models on AWS?
Yes. You’ll use SageMaker to train, tune, and deploy a customer churn model. You’ll also learn how to autoscale endpoints and manage production workloads.
Will this course help with feature engineering and tuning?
Absolutely. You’ll explore real datasets, perform feature analysis, and apply tuning strategies like hyperparameter optimization using SageMaker’s built-in tools.
Does the course include hands-on labs in SageMaker?
Yes. Labs are a core part of the course and include launching Jupyter notebooks, training models, setting hyperparameters, and deploying endpoints in AWS.
Is this course suitable for beginners in SageMaker?
Yes, as long as you have basic Python skills and a foundational understanding of machine learning. No prior experience with SageMaker is required.