Amazon SageMaker: Simplifying Machine Learning Application Development

Machine learning is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market. This course will teach you, an application developer, how to use Amazon SageMaker to simplify the integration of Machine Learning into your applications. Key topics include: an overview of Machine Learning and problems it can help solve, using a Jupyter Notebook to train a model based on SageMaker’s built-in algorithms and, using SageMaker to publish the validated model. You will finish the class by building a serverless application that integrates with the SageMaker published endpoint. Learn from AWS Training and Certification expert instructors through lectures, demonstrations, discussions and hands-on exercises* as we explore this complex topic from the lens of the application developer. *Note that there may be a cost associated with some exercises. If you do not wish to incur additional expenses, you may view demonstrations instead.

• Key problems that Machine Learning can address and ultimately help solve
• How to train a model using Amazon SageMaker’s built-in algorithms and a Jupyter Notebook instance
• How to publish a model using Amazon SageMaker
• How to integrate the published SageMaker endpoint with an application

• Prior application development experience
• Experience with the AWS Console
• Recommended: AWS Developer Professional Series (Building on AWS, Deploying on AWS, Optimizing on AWS)