AWS Healthcare Life Sciences (HCLS) Artificial Intelligence/Machine Learning (AI/ML) Immersion Days offer an opportunity for AWS customers and those who wish to learn about AWS AI/ML services via a deep, hands on workshop experience. Customers can use Immersion Days to:

• Engage in hands on workshops to learn about AI/ML services. We will work in a hands-on fashion with data scientists, machine learning engineers, developers, analysts and anyone else to familiarize the customer with our services. These workshops are hands on -- workshop participants will be provided with temporary AWS account(s) from which they will execute AI/ML workloads in a step-by-step fashion with our HCLS AI/ML Solutions Architects. Please see the Workshops section for available workshops.

• Gain a deep understanding of AWS AI/ML Services. We will discuss what our AI/ML services are, how they can be easily brought to bear on numerous workloads, and help enable the customer to approach their own business problems in the context of AI/ML. These conversations can be overviews of AWS services, or technical deep dives into specific components that to enable well-architected AI/ML applications for HCLS business.

• Understand best practices with AI/ML in the context of HCLS. We will discuss what are the best practices and procedures for using AI/ML intelligently in HCLS applications. This includes basics of training and testing, MLOps and deployment practices, software development life cycle in the context of AI/ML and many other components.

The Immersion Day workshops may be used by in the context of AWS Instructure-Led Labs or self-paced labs. Please see here for more information.

• The AWS Healthcare Life Sciences (HCLS) Artificial Intelligence/Machine Learning (AI/ML) Immersion Days has overviews of a number of the workshops in this repository and instructions for running them.
• The SageMaker Immersion Day provides many other useful workshops.
• The SageMaker sample code repository provides more than 300 code samples for using SageMaker

Do I have to be a machine learning expert to benefit from a workshop?

Absolutely not! These workshops can benefit people at all levels, whether they are machine learning experts, developers, managers, or anyone in your organization. Amazon SageMaker and Amazon's many other machine learning services are designed to remove the heavy lifting from development to quickly enable you to integrate AI/ML into your applications.

How can I get started?

You can peruse this repository for notebooks that are relevant to you.

What workshops makes the most sense for me and my group?

This depends on your teams familiarity with SageMaker. If the team is deeply familiar with ML and SageMaker we recommend picking workshops that best match the business problem(s) you are trying to solve. If your team is not yet deeply familiar with AWS infrastructure and SageMaker, we recommend at least 1 more basic workshop that focuses on tabular analysis so that the team can get hands-on practice with AWS AI/ML steps (e.g. loading data into S3 for training with AI/ML, deploying models etc.)

Who should come to the AWS Instructure-led workshops?

Anyone is welcome to the workshop. We recommend that the customer have at least one developer present who will be actively working on business problems and can take away technical learnings that can be applied for their future work.

How can I get started?

Whether you are doing an AWS Instructure-Led Labs or self-paced labs, we recommend that you begin by looking at the workshops and executing them to get an understanding of SageMaker and the AI/ML services work in the context of healthcare and life sciences.

How do I use these workshops?

The notebooks provided within these workshops are independent units and may be run on their own. Further instructions are provided within each specific directory.

What is the source of these workshops?

Some of these workshops have been created by HCLS AI/ML team has written specific workshops that demonstrate key components of using SageMaker. We have also curated resources from the AWS machine learning blog and the Amazon SageMaker respository of sample code for these workshops.

I am interested in workshops not listed on this repository.

The workshops for the HCLS AI/ML listed are generally focused on applications related to Health and Life Sciences. However, there is a wealth of more general information and public facing AWS provided notebooks that use non-HCLS data here and here.

I think I see a mistake or something I want changed in the repository.

Feel free to to submit a pull request detailing the issue. Please bear with us in if pull requests take longer than expected or are closed.

How can I arrange an AWS Instructor-Led Immersion Day?

If you are interested in having an Immersion Day for your team, please reach out to your AWS Account Manager.

See CONTRIBUTING for more information.

This library is licensed under the MIT-0 License. See the LICENSE file.