Who is the course for
- Developers
- Solutions Architects
- Data Engineers
- Anyone with little to no experience with ML and wants to learn about the
ML pipeline using Amazon SageMaker
What we teach you
In this course, you will learn how to:
- Select and justify the appropriate ML approach for a given business
problem
- Use the ML pipeline to solve a specific business problem
- Train, evaluate, deploy, and tune an ML model using Amazon SageMaker
- Describe some of the best practices for designing scalable,
cost-optimized, and secure ML pipelines in AWS
- Apply machine learning to a real-life business problem after the course is
complete
Required skills
We recommend that attendees of this course have:
- Basic knowledge of Python programming language
- Basic understanding of AWS Cloud infrastructure (Amazon S3 and Amazon
CloudWatch)
- Basic experience working in a Jupyter notebook environment
Teaching methods
Professional explanation with practical samples and examples.
Teaching materials
Amazon Web Services authorized e-book included.