MLOps on AWS

AWS
Cloud
Data and AI
Data Engineering
Machine Learning

With this course, you will discover what MLOps is and how you can apply it in AWS (Amazon Web Services). For example, you will learn more about AWS SageMaker, Elastic Container Service, CloudWatch, and more. This course is aimed at people with Python skills and general ML experience.

Looking to upskill your team(s) or organization?

Rozaliia will gladly help you further with custom training solutions.

Get in touch

What will you learn?

After the training, you will be able to:

Understand all the necessary components in an end-to-end ML system

Set up CloudWatch dashboards for your application

Create and trigger machine learning pipelines with SageMaker

Integrate and deploy all code through a CI/CD pipeline with Github Actions

Deploy your model as scalable API with FastAPI, Docker and ECS Fargate

Program

  • Discover key MLOps principles
  • Create a solution design
  • Get started with the cloud tooling
  • Experiment tracking
  • Training jobs and pipelines

This training is for you if:

Already have a solid understanding of ML, and want to take your models outside of the development phase.

Want to incorporate best practices from Software Engineering

Already have foundational software engineering skills (Python, Git, Docker)

Want to learn more about AWS and MLOps.

This training is not for you if:

Want to learn more about developing ML models in itself, this knowledge is already assumed (check out the Certified Data Science with Python or the Advanced Data Science with Python trainings)

Do not have basic programming experience (check out our Python for Data Analyst course)

Want to learn in more general terms how to develop production-ready applications without working with a specific public cloud (check out our Production-Ready Machine Learning course)

Are mainly interested in doing (exploratory) research. This course is much oriented towards ML engineering

You are interested in trainings about a different public cloud than AWS. Check out our MLOps on Azure and MLOps on GCP trainings.

Why should I do this training?

Learn best practices about deploying machine-learning applications on GCP

Hands-on training with real life examples – learn today apply tomorrow!

Get taught by machine-learning experts that love to teach in a very fun and interactive learning environment

What else should I know?

After registering for this training, you will receive a confirmation email with practical information. A week before the training, the trainer will get in touch to ask you about any requirements you may have and any pre-course tasks you will need to do.

See you soon!

Training information

All literature and course materials are included in the price

Information on the software and tooling will be shared before the start date

This course requires a laptop

Online courses are delivered via Zoom or Microsoft Teams

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