Learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker.
This course walks through the stages of a typical data science process for Machine Learning from analysing and visualising 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 case includes customer retention analysis to inform customer loyalty programs.
What you’ll learn
This course is designed to teach participants 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
AWS at Lumify Work
Lumify Work is an official AWS Training Partner for Australia, New Zealand, and the Philippines. Through our Authorised AWS Instructors, we can provide you with a learning path that’s relevant to you and your organisation, so you can get more out of the cloud. We offer virtual and face-to-face classroom-based training to help you build your cloud skills and enable you to achieve industry-recognised AWS Certification.
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
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