This hands-on course provides a practical introduction to machine learning with Amazon SageMaker AI, AWS’s fully managed service for building, training, and deploying machine learning models. If you’ve ever wanted to take a real dataset, train a machine learning model, deploy it to the cloud, and expose it through a prediction endpoint, this course is for you. We focus on learning by doing. There are no math-heavy lectures, theory-heavy slides, or assumed data science background. Instead, you’ll work through the complete machine learning lifecycle using AWS, Python, and the current SageMaker Python SDK.
We will start by understanding what Amazon SageMaker AI is and how it fits into the modern AWS machine learning ecosystem, including the distinction between Amazon SageMaker AI and the broader Amazon SageMaker platform. Then we’ll move straight into practice.We will see how to configure IAM permissions, launch SageMaker Studio, prepare a real dataset, and upload it to Amazon S3 before training our machine learning model.
