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    The Machine Learning Pipeline on AWS

     Info
    This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem.

    Overview

    Course Objectives

    In this course, you will learn to:

    Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete

    Highlights

    • - The First Authorised Training Partner of AWS with full license in HK
    • - The Most Training Schedules delivered by AWS Authorized Instructors (AAI) and AAI Champion - Best Price Guaranteed
    • - Trained over 50,000 talents in Asia

    Details

    Delivery method

    Deployed on AWS

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    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Support

    Vendor support

    For upcoming schedules or other AWS training enquiries, please contact Kylin Chan at +852 2116 5586 or kylin.chan@kornerstone.comÂ