Requirements

• "Basic Cloud Computing Knowledge: Its essential to have a fundamental understanding of cloud computing concepts and services
• as AWS SageMaker is a cloud-based machine learning platform."
• Machine Learning Fundamentals: A solid understanding of machine learning concepts and algorithms is usually necessary. You should be familiar with supervised and unsupervised learning
• regression
• classification
• and model evaluation.
• Jupyter Notebooks: Many SageMaker courses use Jupyter notebooks for practical exercises. Familiarity with Jupyter notebooks is helpful.

Description

Who this course is for:

• Data Scientists: Data scientists looking to expand their machine learning and data modeling skills with a focus on using AWS SageMaker for developing
• training
• and deploying machine learning models.
• Machine Learning Engineers: Machine learning engineers interested in mastering the tools and techniques within SageMaker to build
• test
• and deploy machine learning models at scale.
• Software Developers: Developers who want to integrate machine learning into their applications and are interested in using SageMaker to streamline model development and deployment.
• Business Analysts: Business analysts looking to gain insights from data using machine learning techniques and SageMaker.
• "AWS Enthusiasts: Those who are already familiar with AWS services and want to explore SageMakers capabilities."