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Jorge Vasquez

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.

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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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Syllabus

Course Overview
Getting Started with AWS SageMaker
Building Machine Learning Models Using AWS SageMaker
Training Machine Learning Models Using AWS SageMaker
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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
Gain hands-on experience and learn about the latest features of Amazon SageMaker through an official workshop.
Browse courses on SageMaker
Show steps
  • Find and register for a SageMaker workshop
  • Attend the workshop and actively participate
Review Python basics
Brush up on the basics of Python syntax and data structures to ensure a strong foundation for this course.
Browse courses on Python
Show steps
  • Review variables, data types, and operators
  • Practice writing simple Python programs
Follow tutorials on Amazon SageMaker
Complete tutorials provided by Amazon to gain hands-on experience with the SageMaker platform.
Browse courses on Amazon SageMaker
Show steps
  • 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
Expand to see all activities and additional details
Show all eight activities
Discuss machine learning concepts with peers
Engage with classmates to exchange ideas, clarify concepts, and enhance understanding of machine learning.
Browse courses on Machine Learning
Show steps
  • 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
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
Show steps
  • Attend industry events and conferences
  • Join online communities and forums
  • Reach out to professionals on LinkedIn
Write a blog post or article about SageMaker
Share your knowledge and insights about Amazon SageMaker by creating a written piece that can benefit the community.
Browse courses on SageMaker
Show steps
  • 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
Apply the concepts learned in the course to create a functional machine learning model using Amazon SageMaker.
Browse courses on Model Development
Show steps
  • 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
Apply your skills in a real-world setting by participating in a Kaggle competition related to machine learning.
Browse courses on Kaggle
Show steps
  • 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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.
Provides a comprehensive guide to machine learning using Python, which can be used as a reference for the coding aspects of this course.
Provides a practical introduction to deep learning using Python, which can be helpful for learners interested in exploring advanced machine learning techniques.
Provides a comprehensive overview of the machine learning landscape, including different algorithms and techniques, which can help learners expand their knowledge beyond this course.
Provides a practical introduction to deep learning using fastai and PyTorch, which can be useful for learners interested in exploring advanced machine learning techniques.
Provides a practical guide to data science, including machine learning, which can be helpful for learners interested in applying these techniques in a business context.
Provides a business-oriented perspective on machine learning, which can be valuable for learners interested in the practical applications of this field.

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