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This course covers the following topics:
Introduction to Amazon SageMaker Studio: An overview of SageMaker Studio’s features, including its integrated Jupyter notebooks, model debugging, and experimentation tools.
Data Preprocessing: Techniques for preparing and cleaning datasets for training and inference.
Model Building and Training: How to build and train machine learning models using SageMaker’s built-in algorithms and AutoML capabilities.
Model Deployment and Monitoring: Deploying models to SageMaker endpoints and monitoring their performance.
Continuous Integration/Continuous Deployment (CI/CD) Pipelines: Automating the process of deploying and updating models in production.
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Hands-on labs for real-world application.
A comprehensive curriculum that covers all aspects of using SageMaker Studio.
Instruction from expert instructors.
A flexible schedule with online and in-person options.
A certification upon completion.
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