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With Amazon Personalize, you can build applications with the machine learning (ML) technology used by Amazon for real-time personalized recommendations. No ML expertise is required.

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With Amazon Personalize, you can build applications with the machine learning (ML) technology used by Amazon for real-time personalized recommendations. No ML expertise is required.

In this course, you will learn how to use Amazon Personalize to build a personalized product experience for your customers. You will learn the basic terminology, important benefits and features, typical use cases, and costs. You will review the solution architecture you can use to build your own recommendation engines and personalization solutions. Through a guided tutorial, you will also build a movie recommendation engine solution in your own Amazon Web Services (AWS) account, which you can further adapt to your use case.

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What's inside

Syllabus

Getting Started with Amazon Personalize

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Developers without ML expertise who want to build personalized product experiences
Beginners and intermediate learners who want to establish or strengthen their foundation in building product recommendations with ML

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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 Getting Started with Amazon Personalize with these activities:
Organize your course materials
Preparation is key to an effective learning experience.
Show steps
  • Gather your course materials
  • Organize your materials into a logical structure
Review the basics of machine learning
Confirm you have the required knowledge before starting the course.
Browse courses on Machine Learning
Show steps
  • Review your notes from previous machine learning courses
  • Complete a machine learning refresher course
Machine Learning for Dummies
Get a solid foundation in machine learning.
Show steps
  • Read the book
  • Complete the practice exercises
Six other activities
Expand to see all activities and additional details
Show all nine activities
Find a mentor in the field of machine learning
Get guidance and support from an experienced professional.
Browse courses on Machine Learning
Show steps
  • Identify potential mentors
  • Reach out to your mentors
Join an Amazon Personalize study group
Connect with other students and learn together.
Browse courses on Amazon Personalize
Show steps
  • Find a study group
  • Participate in the group discussions
Attend an Amazon Personalize workshop
Get hands-on experience with Amazon Personalize.
Browse courses on Amazon Personalize
Show steps
  • Find a workshop
  • Register for the workshop
  • Attend the workshop
Practice using Amazon Personalize
Develop proficiency using Amazon Personalize.
Browse courses on Amazon Personalize
Show steps
  • Follow the Amazon Personalize tutorials
  • Experiment with different recommendation algorithms
Get AWS Certified: Machine Learning - Specialty
Complete this tutorial to get AWS certified in Machine Learning.
Browse courses on Machine Learning
Show steps
  • Enroll in the course
  • Review the course material
  • Take the practice exam
Create a movie recommendation system
Build a movie recommendation system using the skills you learned in this course.
Show steps
  • Gather data on movies
  • Train a recommendation model using Amazon Personalize
  • Deploy the recommendation system

Career center

Learners who complete Getting Started with Amazon Personalize will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning algorithms to solve business problems. This course can help you build a foundation in machine learning, which is a critical skill for Machine Learning Engineers. You will learn about the different types of machine learning algorithms, how to train and evaluate them, and how to deploy them in production. This course can also help you develop the skills you need to work with big data, which is often used in machine learning applications.
Data Scientist
Data Scientists use data to solve business problems. This course can help you build a foundation in data science, which is a critical skill for Data Scientists. You will learn about the different types of data science techniques, how to collect and clean data, and how to analyze and interpret data. This course can also help you develop the skills you need to communicate your findings to stakeholders.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course can help you build a foundation in software engineering, which is a critical skill for Software Engineers. You will learn about the different phases of the software development lifecycle, how to design and implement software architectures, and how to test and debug software. This course can also help you develop the skills you need to work in a team environment.
Product Manager
Product Managers are responsible for the development and launch of new products. This course can help you build a foundation in product management, which is a critical skill for Product Managers. You will learn about the different phases of the product development lifecycle, how to conduct market research, and how to develop and launch new products. This course can also help you develop the skills you need to work with cross-functional teams.
Business Analyst
Business Analysts help organizations improve their business processes. This course can help you build a foundation in business analysis, which is a critical skill for Business Analysts. You will learn about the different types of business analysis techniques, how to collect and analyze data, and how to develop and implement recommendations. This course can also help you develop the skills you need to communicate your findings to stakeholders.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course may be useful for Marketing Managers who want to learn more about how to use machine learning to personalize marketing campaigns. You will learn about the different types of machine learning algorithms that can be used for marketing, how to train and evaluate them, and how to deploy them in production.
Sales Manager
Sales Managers are responsible for leading and managing sales teams. This course may be useful for Sales Managers who want to learn more about how to use machine learning to improve sales performance. You will learn about the different types of machine learning algorithms that can be used for sales, how to train and evaluate them, and how to deploy them in production.
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are successful with a company's products or services. This course may be useful for Customer Success Managers who want to learn more about how to use machine learning to improve customer satisfaction. You will learn about the different types of machine learning algorithms that can be used for customer success, how to train and evaluate them, and how to deploy them in production.
Technical Writer
Technical Writers create documentation for software and other technical products. This course may be useful for Technical Writers who want to learn more about how to use machine learning to improve the quality of their documentation. You will learn about the different types of machine learning algorithms that can be used for technical writing, how to train and evaluate them, and how to deploy them in production.
User Experience Designer
User Experience Designers design the user interface for software and other products. This course may be useful for User Experience Designers who want to learn more about how to use machine learning to improve the user experience. You will learn about the different types of machine learning algorithms that can be used for user experience design, how to train and evaluate them, and how to deploy them in production.
Quality Assurance Analyst
Quality Assurance Analysts test software and other products to ensure that they meet quality standards. This course may be useful for Quality Assurance Analysts who want to learn more about how to use machine learning to improve the quality of their testing. You will learn about the different types of machine learning algorithms that can be used for quality assurance, how to train and evaluate them, and how to deploy them in production.
Project Manager
Project Managers plan and execute projects. This course may be useful for Project Managers who want to learn more about how to use machine learning to improve the success of their projects. You will learn about the different types of machine learning algorithms that can be used for project management, how to train and evaluate them, and how to deploy them in production.
Data Analyst
Data Analysts analyze data to identify trends and patterns. This course may be useful for Data Analysts who want to learn more about how to use machine learning to improve the accuracy of their analysis. You will learn about the different types of machine learning algorithms that can be used for data analysis, how to train and evaluate them, and how to deploy them in production.
Business Development Manager
Business Development Managers identify and develop new business opportunities. This course may be useful for Business Development Managers who want to learn more about how to use machine learning to improve their lead generation and sales performance. You will learn about the different types of machine learning algorithms that can be used for business development, how to train and evaluate them, and how to deploy them in production.
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course may be useful for Financial Analysts who want to learn more about how to use machine learning to improve the accuracy of their recommendations. You will learn about the different types of machine learning algorithms that can be used for financial analysis, how to train and evaluate them, and how to deploy them in production.

Reading list

We've selected eight 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 Getting Started with Amazon Personalize.
Provides a comprehensive overview of machine learning concepts and algorithms, making it a great resource for those who are new to the field.
Covers the fundamentals of deep learning using Python and PyTorch, making it a great resource for those who want to build their own recommendation engines.
Provides a comprehensive overview of information retrieval techniques, including ranking algorithms and evaluation methods.
Provides a comprehensive overview of statistical methods used in data analysis and machine learning, including hypothesis testing, regression analysis, and clustering.
Provides a comprehensive overview of the mathematical foundations of machine learning, including linear algebra, calculus, and optimization.
Provides a comprehensive overview of Bayesian reasoning and its applications in machine learning.
Provides a comprehensive overview of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Provides a practical guide to machine learning, covering topics such as data preprocessing, feature engineering, and model evaluation.

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