Practical Data Science with Amazon SageMaker
Learn how to solve a real-world use case with machine learning using Amazon SageMaker
In this intermediate-level course, you will learn how to solve a real-world use case with machine learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for machine learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. A real life use case includes customer retention analysis to inform customer loyalty programs.
What you'll learn
- Prepare a dataset for training
- Train and evaluate a machine learning model
- Automatically tune a machine learning model
- Prepare a machine learning model for production
- And much more
About this course
Who should take this course
- Developers
- Data scientists
What experience you'll need
- Familiarity with Python programming language
- Basic understanding of machine learning
AboutAppsbroker Academy
Appsbroker Academy is an Authorised Training Partner for Google Cloud. Drawing on our own highly skilled engineers’ unique experiences and expertise, we provide dedicated, industry-specific training using real-life examples to help your people to thrive.
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