Practical Data Science with Amazon SageMaker Training

Live Online & Classroom Enterprise Certification Training

As artificial intelligence and machine learning (AI/ML) are quickly becoming part of our day-to-day, it is becoming increasingly more important to understand how to collaborate efficiently with data scientists and build applications that integrate with ML. The Practical Science with Amazon SageMaker course will help you in your developer or DevOps engineer role understand the basics of ML and the steps involved in building ML models using Amazon SageMaker Studio. In this one-day, classroom training course an expert AWS instructor will walk you through how to prepare data and train, evaluate, tune, and deploy ML models.

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What is Practical Data Science with Amazon SageMaker Certification Training about?

Artificial intelligence and machine learning (AI/ML) are becoming mainstream. In this course, you will spend a day in the life of a data scientist so that you can collaborate efficiently with data scientists and build applications that integrate with ML. You will learn the basic process data scientists use to develop ML solutions on Amazon Web Services (AWS) with Amazon SageMaker. You will experience the steps to build, train, and deploy an ML model through instructor-led demonstrations and labs.

What are the objectives of Practical Data Science with Amazon SageMaker Certification Training ?

In this course, you will learn to:

Discuss the benefits of different types of machine learning for solving business problems
Describe the typical processes, roles, and responsibilities on a team that builds and deploys ML systems
Explain how data scientists use AWS tools and ML to solve a common business problem
Summarize the steps a data scientist takes to prepare data
Summarize the steps a data scientist takes to train ML models
Summarize the steps a data scientist takes to evaluate and tune ML models
Summarize the steps to deploy a model to an endpoint and generate predictions
Describe the challenges for operationalizing ML models
Match AWS tools with their ML function

Who is Practical Data Science with Amazon SageMaker Certification Training for?

This course is intended for:

Development Operations (DevOps) engineers
Application developers

What are the prerequisites for Practical Data Science with Amazon SageMaker Certification Training?

We recommend that attendees of this course have:

AWS Technical Essentials
Entry-level knowledge of Python programming
Entry-level knowledge of statistics

Available Training Modes

Live Online Training

1 Days

Course Outline Expand All

Expand All

Introduction to Machine Learning

Benefits of machine learning (ML)

Types of ML approaches

Framing the business problem

Prediction quality

Processes, roles, and responsibilities for ML projects

Preparing a Dataset

Data analysis and preparation

Data preparation tools

Demonstration: Review Amazon SageMaker Studio and Notebooks

Hands-On Lab: Data Preparation with SageMaker Data Wrangler

Training a Model

Steps to train a model

Choose an algorithm

Train the model in Amazon SageMaker

Hands-On Lab: Training a Model with Amazon SageMaker

Amazon CodeWhisperer

Demonstration: Amazon CodeWhisperer in SageMaker Studio Notebooks

Evaluating and Tuning a Model

Model evaluation

Model tuning and hyperparameter optimization

Hands-On Lab: Model Tuning and Hyperparameter Optimization with Amazon SageMaker

Deploying a Model

Model deployment

Hands-On Lab: Deploy a Model to a Real-Time Endpoint and Generate a Prediction

Operational Challenges

Responsible ML

ML team and MLOps

Automation

Monitoring

Updating models (model testing and deployment)

Other Model-Building Tools

Different tools for different skills and business needs

No-code ML with Amazon SageMaker Canvas

Demonstration: Overview of Amazon SageMaker Canvas

Amazon SageMaker Studio Lab

Demonstration: Overview of SageMaker Studio Lab

(Optional) Hands-On Lab: Integrating a Web Application with an Amazon SageMaker Model Endpoint

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Who is the instructor for this training?

The trainer for this Practical Data Science with Amazon SageMaker Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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