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David Tucker

Training a machine learning model is only the first step. This course will teach you how to deploy, monitor, and scale your machine learning solution in preparation for the Machine Learning Specialty exam.

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Training a machine learning model is only the first step. This course will teach you how to deploy, monitor, and scale your machine learning solution in preparation for the Machine Learning Specialty exam.

Machine Learning Implementation and Operations is one of the four domains covered by the AWS Machine Learning Specialty certification exam. In this course, Implementing and Operating AWS Machine Learning Solutions, you’ll learn key areas from this domain that are covered in the exam. First, you’ll explore the different AWS services that can support a machine learning solution in production. Next, you’ll discover how to deploy and scale a machine learning model with Amazon Sagemaker. Finally, you’ll learn how to implement security best practices for your machine learning solution with AWS. When you’re finished with this course, you’ll have the skills and knowledge in this domain needed to prepare for the AWS Machine Learning Specialty certification exam.

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What's inside

Syllabus

Course Overview
AWS Machine Learning Services
Deploying a SageMaker Model
Securing a SageMaker Implementation
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Implementing a Highly-available Machine Learning Solution

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores Amazon Machine Learning Services, which are standard in industry
Teaches AWS Machine Learning Specialty Preparation, which helps students prepare for their exam
Offers hands-on labs and interactive materials, which provide experience and practice
Covers Amazon Web Services, which are highly relevant in industry
Offers a comprehensive study of AWS Machine Learning, which provides depth and breadth

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Implementing and Operating AWS Machine Learning Solutions with these activities:
Review DevOps Principles
Understanding DevOps principles will help ensure your solution is scalable and easy to manage.
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Show steps
  • Review the DevOps Lifecycle
  • Research CI/CD
  • Practice with a CI/CD Tool
Review Machine Learning Basics
Reviewing the basics of machine learning will help you understand the concepts covered in this course more easily.
Browse courses on Supervised Learning
Show steps
  • Read articles or watch videos about machine learning concepts.
  • Take a practice quiz on machine learning.
  • Review your notes from previous machine learning courses.
AWS Documentation Drills
Good documentation is essential for succeeding as a cloud engineer and practitioner.
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  • Find the AWS Documentation for SageMaker
  • Locate the API Reference
  • Find the Documentation for a Specific API
  • Practice using the API using the SDK
Seven other activities
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Follow Online Tutorials
Following online tutorials will help you learn about specific machine learning topics in a structured and interactive way.
Browse courses on Online Learning
Show steps
  • Find a set of online tutorials that cover the topics you want to learn about.
  • Follow the tutorials step-by-step.
  • Complete the exercises and quizzes included in the tutorials.
Join a Study Group
Joining a study group will allow you to discuss the course material with other students and get help with difficult concepts.
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Show steps
  • Find a study group that meets regularly.
  • Attend study group meetings and participate in discussions.
  • Help other students understand the material.
Amazon SageMaker Pricing Walkthrough
Understanding pricing will help you plan for expenses down the road and help you make good choices for your budget.
Browse courses on AWS SageMaker
Show steps
  • Visit the SageMaker Pricing Page
  • Review the Pricing Tiers
  • Estimate Costs Using the Calculator
Create a Machine Learning Model
Creating your own machine learning model will help you apply the concepts you learn in this course and gain practical experience.
Show steps
  • Choose a dataset to use for your model.
  • Select a machine learning algorithm and train your model.
  • Evaluate the performance of your model.
  • Deploy your model to a production environment.
Solve Practice Problems
Solving practice problems will help you improve your understanding of machine learning algorithms and how to apply them to real-world problems.
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Show steps
  • Check your answers against the provided solutions.
  • Find a set of practice problems online or in a textbook.
  • Solve the problems on your own.
Deploying a Custom SageMaker Model
Deploying a custom SageMaker model will deepen your understanding of the deployment process, reinforce learning of AWS services, and allow you to build a solution that you can use to expand on.
Browse courses on SageMaker
Show steps
  • Create a SageMaker Model
  • Configure a SageMaker Endpoint
  • Use Boto3 to Deploy the Model
Developing a Machine Learning Pipeline
Developing your own machine learning pipeline will significantly advance your mastery when it comes to working with machine learning models.
Browse courses on Machine Learning
Show steps
  • Define the Business Problem
  • Gather and Prepare Data
  • Select and Train a Model
  • Deploy the Model
  • Monitor and Evaluate the Pipeline

Career center

Learners who complete Implementing and Operating AWS Machine Learning Solutions will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
The Implementing and Operating AWS Machine Learning Solutions course can also be very useful for Machine Learning Engineers. This course will provide you with the in-depth knowledge you need to build and manage machine learning solutions in production. The course covers a wide range of topics, including deploying machine learning models, managing data, and monitoring and troubleshooting machine learning systems. This course can also help you to prepare for the AWS Machine Learning Specialty certification exam, which is a valuable credential for Machine Learning Engineers.
Data Scientist
The Implementing and Operating AWS Machine Learning Solutions course fits well into the Data Scientist career. This course will provide you with the skills and knowledge needed to deploy and manage machine learning models in production, which is a key part of the Data Scientist job role. This course can also help you to prepare for the AWS Machine Learning Specialty certification exam, which is a valuable credential for Data Scientists.
DevOps Engineer
The Implementing and Operating AWS Machine Learning Solutions course may also be useful for DevOps Engineers who want to learn how to deploy and manage machine learning solutions in production. This course covers a wide range of topics, including deploying machine learning models, managing data, and monitoring and troubleshooting machine learning systems. This course can help DevOps Engineers to build and maintain reliable and scalable machine learning solutions.
Data Architect
The Implementing and Operating AWS Machine Learning Solutions course may also be useful for Data Architects who want to learn how to design and manage data pipelines for machine learning solutions. This course covers a wide range of topics, including data modeling, data integration, and data governance. This course can help Data Architects to build and maintain reliable and scalable data pipelines for machine learning solutions.
Cloud Architect
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Cloud Architects who want to learn how to design and manage cloud infrastructure for machine learning solutions. This course covers a wide range of topics, including cloud computing concepts, cloud security, and cloud networking. This course can help Cloud Architects to build and maintain reliable and scalable cloud infrastructure for machine learning solutions.
Software Architect
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Software Architects who want to learn how to design and manage software systems for machine learning solutions. This course covers a wide range of topics, including software design patterns, software development methodologies, and software testing. This course can help Software Architects to build and maintain reliable and scalable software systems for machine learning solutions.
IT Manager
The Implementing and Operating AWS Machine Learning Solutions course may be useful for IT Managers who want to learn how to manage machine learning projects. This course covers a wide range of topics, including project management, risk management, and change management. This course can help IT Managers to successfully manage machine learning projects.
Security Engineer
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Security Engineers who want to learn how to secure machine learning solutions. This course covers a wide range of topics, including information security, cloud security, and machine learning security. This course can help Security Engineers to implement security best practices for machine learning solutions.
Network Engineer
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Network Engineers who want to learn how to design and manage networks for machine learning solutions. This course covers a wide range of topics, including network architectures, network protocols, and network security. This course can help Network Engineers to build and maintain reliable and scalable networks for machine learning solutions.
Systems Engineer
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Systems Engineers who want to learn how to design and manage systems infrastructure for machine learning solutions. This course covers a wide range of topics, including cloud computing concepts, cloud security, and cloud networking. This course can help Systems Engineers to build and maintain reliable and scalable systems infrastructure for machine learning solutions.
Business Analyst
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Business Analysts who want to learn how to use machine learning to solve business problems. This course covers a wide range of topics, including machine learning concepts, machine learning algorithms, and machine learning applications. This course can help Business Analysts to make better use of machine learning to solve business problems.
Data Analyst
The Implementing and Operating AWS Machine Learning Solutions course may also be useful for Data Analysts who want to learn how to analyze data for machine learning solutions. This course covers a wide range of topics, including data analysis techniques, data visualization, and data mining. This course can help Data Analysts to build and maintain reliable and scalable data pipelines for machine learning solutions.
Database Administrator
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Database Administrators who want to learn how to manage databases for machine learning solutions. This course covers a wide range of topics, including database design, database administration, and database security. This course can help Database Administrators to build and maintain reliable and scalable databases for machine learning solutions.
Product Manager
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Product Managers who want to learn how to develop and manage machine learning products. This course covers a wide range of topics, including machine learning concepts, machine learning algorithms, and machine learning applications. This course can help Product Managers to make better use of machine learning to develop and manage machine learning products.
Data Engineer
The Implementing and Operating AWS Machine Learning Solutions course may be useful for Data Engineers who want to learn how to design and manage data pipelines for machine learning solutions. This course covers a wide range of topics, including data modeling, data integration, and data governance. This course can help Data Engineers to build and maintain reliable and scalable data pipelines for machine learning solutions.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Implementing and Operating AWS Machine Learning Solutions.
Offers a comprehensive theoretical foundation in machine learning, making it a valuable resource for those seeking a deeper understanding of the underlying principles.
Serves as a comprehensive reference for deep learning with Python, offering additional depth and practical implementation details.
Is frequently used as a supplemental reference for practical machine learning implementation.

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