Registration

Practical Data Science with Amazon SageMaker

Course Code: AWS-PDSASM
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Duration: 1 Hours
Available Formats: iMVP (Remote)
Date: 06-22-2021 - 06-22-2021

Time: 09:00 AM - 05:00 PM EDT (UTC - 4)


Price: 675 USD - 800 CAD

About Course

In this intermediate-level course, individuals learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. Real life use cases include customer retention analysis to inform customer loyalty programs.

Prerequisite Courses


Skills Gained

  • 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

Who Can Benefit

  • Developers
  • Data Scientists

Course Details


  • Types of ML
  • Job Roles in ML
  • Steps in the ML pipeline

Module 1: Introduction to Machine Learning



Module 2: Introduction to Data Prep and SageMaker
  • Training and Test dataset defined
  • Introduction to SageMaker
  • Demo: SageMaker console
  • Demo: Launching a Jupyter notebook


Module 3: Problem formulation and Dataset Preparation
  • Business Challenge: Customer churn
  • Review Customer churn dataset

Course Registration

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