Practical Data Science on the AWS Cloud Specialization
Become a cloud data science expert. Develop and scale your data science projects into the cloud using Amazon SageMaker
Skills you will gain
About this Specialization
Applied Learning Project
By the end of this Specialization, you will be ready to:
• Ingest, register, and explore datasets
• Detect statistical bias in a dataset
• Automatically train and select models with AutoML
• Create machine learning features from raw data
• Save and manage features in a feature store
• Train and evaluate models using built-in algorithms and custom BERT models
• Debug, profile, and compare models to improve performance
• Build and run a complete ML pipeline end-to-end
• Optimize model performance using hyperparameter tuning
• Deploy and monitor models
• Perform data labeling at scale
• Build a human-in-the-loop pipeline to improve model performance
• Reduce cost and improve performance of data products
How the Specialization Works
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
Frequently Asked Questions
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More questions? Visit the Learner Help Center.