Practical Data Science with Amazon SageMaker

Course Overview

In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment.

Schedule

Start DateDelivery FormatDaysTimeStatusPriceEnroll
Comming SoonLive Virtual Led110:00 amEnrolling Now$675
Comming SoonLive Virtual Led110:00 amEnrolling Now$675
Comming SoonLive Virtual Led110:00 amEnrolling Now$675
Comming SoonLive Virtual Led110:00 amEnrolling Now$675

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Who Should Attend

This course is intended for:

  • A technical audience at an intermediate level

Prerequisites

We recommend that attendees of this course have the following prerequisites:

  • Working knowledge of a programming language

Objectives

Using Amazon SageMaker, this course teaches you how to:

  • Prepare a dataset for training.
  • Train and evaluate a machine learning model.
  • Automatically tune a machine learning model.
  • Prepare a machine learning model for production.
  • Think critically about machine learning model results.

Course Outline