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Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1

In this course, you are going to learn the skills you need to build, train, and deploy machine learning models in Amazon SageMaker, including how to create REST APIs to integrate them into your applications for solving real-world problems.

A fully managed machine learning service is a great place to start if you want to quickly get machine learning into your applications. In this course, Build, Train, and Deploy Machine Learning Models with Amazon SageMaker, you will gain the ability to create machine learning models in Amazon SageMaker and to integrate them into your applications. First, you’ll learn the basics and how to set up SageMaker. Next, you’ll discover how to build, train, and deploy models applied to Image Classification for breast cancer detection and how to integrate them into a REST API. Finally, you will even discover how to manage security and scalability in Amazon SageMaker. When you’re finished with this course, you will have a foundational understanding of Amazon SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

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What's inside

Syllabus

Course Overview

Getting Started with AWS SageMaker

Building Machine Learning Models Using AWS SageMaker

Training Machine Learning Models Using AWS SageMaker

Deploying Machine Learning Models Using AWS SageMaker

Managing Security and Scalability in AWS SageMaker

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a solid foundation in Amazon SageMaker that benefits learners as they create machine learning-enabled applications

Taught by Jorge Vasquez, who is recognized for their expertise in the field of machine learning

Examines machine learning and its applications, which is highly relevant in the field of computer science

Develops foundational skills in building, training, and deploying machine learning models, which are core for a variety of roles

Specifically applicable to solving real-world, machine learning-based problems encountered in the fields of computer science and software development

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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 Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1 with these activities:

Attend an Amazon SageMaker workshop

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Gain hands-on experience and learn about the latest features of Amazon SageMaker through an official workshop.

Browse courses on SageMaker

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Find and register for a SageMaker workshop
Attend the workshop and actively participate

Review Python basics

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Brush up on the basics of Python syntax and data structures to ensure a strong foundation for this course.

Browse courses on Python

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Review variables, data types, and operators
Practice writing simple Python programs

Follow tutorials on Amazon SageMaker

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Complete tutorials provided by Amazon to gain hands-on experience with the SageMaker platform.

Browse courses on Amazon SageMaker

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Find tutorials on AWS Documentation or YouTube
Follow the instructions to create and train a model
Deploy the model and test its accuracy

Five other activities

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Discuss machine learning concepts with peers

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Engage with classmates to exchange ideas, clarify concepts, and enhance understanding of machine learning.

Browse courses on Machine Learning

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Find a study group or online forum
Participate in discussions and ask questions
Share knowledge and insights with others

Network with professionals in the field

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Connect with individuals in the industry to expand your knowledge, learn about career opportunities, and stay updated with the latest trends.

Browse courses on Networking

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Attend industry events and conferences
Join online communities and forums
Reach out to professionals on LinkedIn

Write a blog post or article about SageMaker

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Share your knowledge and insights about Amazon SageMaker by creating a written piece that can benefit the community.

Browse courses on SageMaker

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Choose a topic and gather information
Write a clear and concise article
Publish your article on a blog or platform

Build a machine learning model using SageMaker

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Apply the concepts learned in the course to create a functional machine learning model using Amazon SageMaker.

Browse courses on Model Development

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Choose a dataset and define the problem
Prepare the data and create a SageMaker notebook
Train and evaluate the model
Deploy the model and monitor its performance

Participate in a Kaggle competition

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Apply your skills in a real-world setting by participating in a Kaggle competition related to machine learning.

Browse courses on Kaggle

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Find a suitable competition on Kaggle
Download the data and familiarize yourself with the problem
Develop and train your model
Submit your results and analyze your performance

Career center

Learners who complete Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1 will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and implementing machine learning models. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use data to solve business problems. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Data Scientist.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software applications. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Software Engineer.

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Cloud Engineer

Cloud Engineers design, build, and maintain cloud-based applications. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Cloud Engineer.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Data Analyst.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Financial Analyst.

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Risk Analyst

Risk Analysts assess and manage risk for businesses. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Risk Analyst.

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Product Manager

Product Managers are responsible for the development and launch of new products. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Product Manager.

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Data Engineer

Data Engineers design and build data pipelines to store and process data. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Data Engineer.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Quantitative Analyst.

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Actuary

Actuaries use mathematical and statistical models to assess risk and develop insurance policies. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as an Actuary.

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Software Developer

Software Developers design, develop, and maintain software applications. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Software Developer.

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Business Analyst

Business Analysts use data to solve business problems. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Business Analyst.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to improve the efficiency of operations. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as an Operations Research Analyst.

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Statistician

Statisticians collect, analyze, and interpret data. This course will help you build a foundation in Amazon SageMaker, a managed machine learning service that will allow you to create, train, and deploy models quickly and efficiently. You will learn how to use SageMaker's built-in algorithms and how to integrate your own models into SageMaker. This course will give you the skills you need to succeed as a Statistician.

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Reading list

We've selected 11 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 Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1.

Machine Learning Con Pytorch Y Scikit Lean

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Provides a comprehensive guide to machine learning using Python, which can be used as a reference for the coding aspects of this course.

Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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