AI Engineering: Build, Train, Fine-Tune and Deploy Models with AWS SageMaker

Source: https://zerotomastery.io/courses/ai-engineer-bootcamp-aws-sagemaker/

What Is An AI Engineer?

The short version is that an AI Engineer works on the entire lifecycle of an AI application – that is, an application that utilizes AI at its core. An AI Engineer takes AI models, including Large Language Models, and customizes them to their needs.

That requires everything from building models using custom datasets, to training and tuning models, to deploying models and scaling them using cloud technologies.

The role is growing like wildfire, but it’s still evolving and will no doubt continue evolving as the AI landscape changes.

What Is AWS SageMaker?

AWS SageMaker (also referred to as Amazon SageMaker) is a fully managed machine learning service that empowers you to quickly build, train, fine-tune and deploy machine learning models at scale. It eliminates the heavy lifting of infrastructure management, so you can focus on the fun part – creating your own awesome AI projects and applications!

In short, it’s one of the leading, real-world AI tools used by AI Engineers, Machine Learning Engineers, Developers and Data Scientists.

Want to know why makes AWS SageMaker really cool though?

It allows end-to-end machine learning in a way that’s easy to use, no matter your skill level!

So whether you’re a seasoned AI expert or just getting started, SageMaker offers intuitive tools and a user-friendly interface that make machine learning accessible to everyone.

If you’re looking to build and deploy your own AI applications, this is the place to be.