Practical Data Science with Amazon SageMaker (PDSASM)

 

Who should attend

  • Developers
  • Data Scientists

Certifications

This course is part of the following Certifications:

Prerequisites

  • 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

Course Content

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.

Prices & Delivery methods

Online Training

Duration
1 day

Price
  • on request
Classroom Training

Duration
1 day

Price
  • on request

Click on town name or "Online Training" to book Schedule

Europe

Czech Republic

Online Training This is a FLEX course in English language. Time zone: Central European Summer Time (CEST)

North Macedonia

Online Training This is a FLEX course in English language. Time zone: Central European Time (CET)

United Kingdom

Online Training Time zone: British Summer Time (BST) Course language: English
Online Training Time zone: British Summer Time (BST) Course language: English
Online Training Time zone: Greenwich Mean Time (GMT) Course language: English
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.
This is a FLEX course, which is delivered both virtually and in the classroom.