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The Machine Learning Pipeline on AWS

Course Code: AWS-ML-PL | Duration: 4 Hours
Available Formats: Remote
Date: 05/20/2024 - 05/20/2024

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

Price: 2,700 USD - 3,200 CAD

About Course

Learn how to use the machine learning ML pipeline with Amazon SageMaker with hands on exercises and four days of instruction You will learn how to frame your business problems as ML problems and use Amazon SageMaker to train evaluate tune and deploy ML models Hands on learning is a key component of this course so you ll choose a project to work on and then apply the knowledge and skills you learn to your chosen project in each phase of the pipeline You ll have a choice of projects fraud detection recommendation engines or flight delays


Prerequisite Courses

Basic knowledge of Python Basic understanding of working in a Jupyter notebook environment Basic understanding of AWS Cloud infrastructure Amazon S3 and Amazon CloudWatch Take this skills assessment to see if you have the required knowledge to skip AWS Technical Essentials the first course in the AWS technical training path https www exitcertified com training resources skills assessments aws skills assessment


Skills Gained

Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train evaluate deploy and tune an ML model in Amazon SageMaker Describe some of the best practices for designing scalable cost optimized and secure ML pipelines in AWS Apply machine learning to a real life business problem after the course is complete


Who Can Benefit

Developers Solutions architects Data engineers Anyone who wants to learn about the ML pipeline via Amazon SageMaker even if you have little to no experience with machine learning


Course Details

Day 1Module 0 Introduction Module 1 Introduction to Machine Learning and the ML Pipeline Module 2 Introduction to Amazon SageMaker Module 3 Problem Formulation Day 2Module 3 Problem Formulation continued Module 4 Preprocessing Day 3 Module 5 Model Training Module 6 Model Evaluation

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