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AWS Discovery Days - Machine Learning Basics

13 Feb 2026   06:00 PM CST

  • Free Webinar
  • Live Q&A
  • Free Participation Certificate
  • Learn from Industry Experts

Learn More About This Topic

Webinar Overview
AWS’s Machine Learning Basics webinar provides an overview of how ML works and how AWS simplifies each stage of the workflow. It introduces key concepts such as data preparation, training, evaluation, and deployment, then maps them to AWS tools. The session highlights AI Services for plug-and-play intelligence and Amazon SageMaker for end-to-end model development, automation, and scalable inference. A brief demo typically shows loading data into S3, training a model in SageMaker, and deploying an endpoint. The webinar closes with guidance on choosing the right service, managing costs, and applying best practices for reliable, production-ready ML systems.
Key Points

  • AWS ML Stack: AI Services (prebuilt APIs), Amazon SageMaker (end-to-end ML platform), and ML frameworks on AWS infrastructure.
  • Core Concepts: Data preparation, model training, validation, evaluation metrics, and deployment.
  • SageMaker Focus: Simplifies notebooks, training jobs, tuning, deployment, and monitoring with fully managed tooling.
  • Use Cases: Image analysis, NLP, forecasting, recommendations, and automation.
  • Best Practices: Start small with AI services, leverage automation, optimize costs, and adopt MLOps for reliable production workflows.
Meet The Trainer
Sachin Chauhan
Sachin Chauhan

IT Professional with over 16 years of experience in the Microsoft .NET framework, adept at Microsoft Azure, AI, Cognitive Services, ASP.NET Core MVC, C#, HTML5, CSS3, JavaScript, Angular, ReactJs, and SharePoint (2007-2016).

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Webinar Summary:

AWS’s Machine Learning Basics webinar provides an overview of how ML works and how AWS simplifies each stage of the workflow. It introduces key concepts such as data preparation, training, evaluation, and deployment, then maps them to AWS tools. The session highlights AI Services for plug-and-play intelligence and Amazon SageMaker for end-to-end model development, automation, and scalable inference. A brief demo typically shows loading data into S3, training a model in SageMaker, and deploying an endpoint. The webinar closes with guidance on choosing the right service, managing costs, and applying best practices for reliable, production-ready ML systems.

13 Feb 2026 | 06:00 PM CST   3 Hours

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