Practical Data Science with Amazon SageMaker (PDSASM)


Course Overview

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.

Who should attend

  • Developers
  • Data Scientists


This course is part of the following Certifications:


  • Familiarity with Python programming language
  • Basic understanding of Machine Learning

Course Objectives

  • 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

Follow On Courses

Prices & Delivery methods

Online training

1 day

  • 750,– €
Classroom training

1 day

  • Sverige: 750,– €



Time zone: Central European Time (CET)   ±1 hour

Online training Time zone: Greenwich Mean Time (GMT) Course language: English guaranteed!
Online training Time zone: Greenwich Mean Time (GMT) Course language: English
Online training Time zone: British Summer Time (BST) Course language: English
Guaranteed date:   We will carry out all guaranteed training regardless of the number of attendees, exempt from force majeure or other unexpected events, like e.g. accidents or illness of the trainer, which prevent the course from being conducted.
Instructor-led Online Training:   This is an Instructor-Led Online course