The Machine Learning Pipeline on AWS Course

Course Code: GK7376

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Duration: 4 days

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Course Overview

The Machine Learning Pipeline on AWS is a project-based course that takes delegates through the complete machine learning lifecycle using Amazon SageMaker. Delegates learn each stage of the pipeline and then apply those skills to a practical business problem such as fraud detection, recommendation engines or flight-delay prediction.

By the end of the course, delegates will have built, trained, evaluated, tuned and deployed a machine learning model using AWS services.

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Target Audience

• Developers
• Solutions Architects
• Data Engineers
• IT professionals who want to understand machine learning pipelines on AWS
• Professionals with little or no previous machine learning experience who want practical experience with Amazon SageMaker

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Course Objectives

• Select and justify an appropriate machine learning approach for a business problem.
• Use the machine learning pipeline to solve a specific business problem.
• Train, evaluate, deploy and tune a machine learning model using Amazon SageMaker.
• Apply best practices for scalable, cost-optimised and secure machine learning pipelines on AWS.
• Apply machine learning concepts to a practical project using the AWS Cloud.

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Course Content

Day 1

• Introduction to machine learning and the ML pipeline
• Amazon SageMaker and Jupyter notebooks
• Problem formulation
• Converting business problems into ML problems
• Amazon SageMaker Ground Truth

Day 2

• Data collection and preprocessing
• Data visualisation
• Choosing an appropriate algorithm
• Preparing and splitting data for training
• Training jobs in Amazon SageMaker

Day 3

• Model evaluation
• Classification and regression metrics
• Model training and evaluation project work
• Feature engineering
• Hyperparameter tuning

Day 4

• Feature engineering and model tuning project work
• Deploying models
• Inference and model monitoring
• Amazon SageMaker endpoints
• Final project presentation and course review

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Course Prerequisites

• Basic knowledge of Python programming
• Basic understanding of AWS Cloud infrastructure, including Amazon S3 and Amazon CloudWatch
• Basic experience working with Jupyter notebooks

AWS Cloud Practitioner Essentials or equivalent AWS knowledge is recommended.

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Certification

This is an AWS skills-based training course. No certification exam is included in the course fee.

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Note - This course is delivered via our training partner Global Knowledge.