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AWS
Learn how Amazon SageMaker mitigates the core challenges of implementing a machine learning pipeline. In this course, you learn how SageMaker notebooks and instances help power your machine learning workloads and review key Amazon SageMaker features.
Read more
Learn how Amazon SageMaker mitigates the core challenges of implementing a machine learning pipeline. In this course, you learn how SageMaker notebooks and instances help power your machine learning workloads and review key Amazon SageMaker features.
Read more
Learn how Amazon SageMaker mitigates the core challenges of implementing a machine learning pipeline. In this course, you learn how SageMaker notebooks and instances help power your machine learning workloads and review key Amazon SageMaker features.
Learn how Amazon SageMaker mitigates the core challenges of implementing a machine learning pipeline. In this course, you learn how SageMaker notebooks and instances help power your machine learning workloads and review the key Amazon SageMaker features.
Register for this course and see more details by visiting:
OpenCourser.com/course/0c823n/aws
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What's inside
Syllabus
AWS Foundations: How Amazon SageMaker Can Help
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Designed for learners who have experience working with machine learning but less experience working with AI
Course is industry standard and is taught by Amazon experts
Taught by AWS, an industry expert in cloud services
Offers a comprehensive study of Amazon SageMaker features and services
Develops skills and knowledge highly relevant to cloud computing
Assumes basic knowledge of machine learning
May be less suitable for learners who are complete beginners in machine learning
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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 AWS Foundations: How Amazon SageMaker Can Help with these
activities:
AWS SageMaker Resource Compilation
Show steps
Create a collection of resources related to AWS SageMaker to support your learning.
Browse courses on
AWS SageMaker
Show steps
-
Gather links to relevant documentation, tutorials, and videos.
-
Organize the resources into categories or topics.
-
Review the resources regularly to reinforce your understanding.
Amazon SageMaker Guided Labs
Show steps
Practice building and deploying machine learning models on AWS SageMaker to solidify your understanding of the platform's capabilities.
Browse courses on
AWS SageMaker
Show steps
-
Follow the step-by-step instructions in the labs.
-
Experiment with different parameters and observe the impact on model performance.
-
Troubleshoot any errors you encounter.
AWS SageMaker Notebooks Tutorial
Show steps
Complete the interactive tutorial to learn how to use SageMaker notebooks to build and train machine learning models.
Browse courses on
AWS SageMaker
Show steps
-
Follow the steps in the tutorial.
-
Create a SageMaker notebook instance.
-
Import data and build a machine learning model in the notebook.
-
Deploy the model as an endpoint.
Three other activities
Expand to see all activities and additional details
Show all six activities
AWS SageMaker Study Group
Show steps
Join or start a study group to collaborate with other students and reinforce your understanding by teaching others.
Browse courses on
AWS SageMaker
Show steps
-
Find or create a study group.
-
Meet regularly to discuss course material.
-
Take turns presenting concepts to the group.
-
Help other students with their questions.
AWS SageMaker Machine Learning Project
Show steps
Build a machine learning project using AWS SageMaker to apply your skills and demonstrate your understanding.
Browse courses on
AWS SageMaker
Show steps
-
Define the problem you want to solve.
-
Gather and prepare your data.
-
Choose and train a machine learning model.
-
Deploy the model as an endpoint.
-
Evaluate the performance of your model.
AWS SageMaker Blog Post
Show steps
Write a blog post about your experience using AWS SageMaker to share your knowledge and insights with others.
Browse courses on
AWS SageMaker
Show steps
-
Choose a topic that you're familiar with.
-
Write a clear and concise blog post that is helpful to others.
-
Publish your blog post on a relevant platform.
AWS SageMaker Resource Compilation
Show steps
Create a collection of resources related to AWS SageMaker to support your learning.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Gather links to relevant documentation, tutorials, and videos.
- Organize the resources into categories or topics.
- Review the resources regularly to reinforce your understanding.
Amazon SageMaker Guided Labs
Show steps
Practice building and deploying machine learning models on AWS SageMaker to solidify your understanding of the platform's capabilities.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Follow the step-by-step instructions in the labs.
- Experiment with different parameters and observe the impact on model performance.
- Troubleshoot any errors you encounter.
AWS SageMaker Notebooks Tutorial
Show steps
Complete the interactive tutorial to learn how to use SageMaker notebooks to build and train machine learning models.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Follow the steps in the tutorial.
- Create a SageMaker notebook instance.
- Import data and build a machine learning model in the notebook.
- Deploy the model as an endpoint.
Three other activities
Expand to see all activities and additional details
Show all six activities
AWS SageMaker Study Group
Show steps
Join or start a study group to collaborate with other students and reinforce your understanding by teaching others.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Find or create a study group.
- Meet regularly to discuss course material.
- Take turns presenting concepts to the group.
- Help other students with their questions.
AWS SageMaker Machine Learning Project
Show steps
Build a machine learning project using AWS SageMaker to apply your skills and demonstrate your understanding.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Define the problem you want to solve.
- Gather and prepare your data.
- Choose and train a machine learning model.
- Deploy the model as an endpoint.
- Evaluate the performance of your model.
AWS SageMaker Blog Post
Show steps
Write a blog post about your experience using AWS SageMaker to share your knowledge and insights with others.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Choose a topic that you're familiar with.
- Write a clear and concise blog post that is helpful to others.
- Publish your blog post on a relevant platform.
Career center
Learners who complete AWS Foundations: How Amazon SageMaker Can Help will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers work on various aspects of building and managing machine learning models. They collaborate with data scientists and software engineers to bring these models to production. This course may be useful as it provides an overview of Amazon SageMaker, a platform that helps automate and simplify the process of building, training, and deploying machine learning models.
Data Scientist
Data Scientist
Data Scientists build, train, and evaluate machine learning models to solve various business problems. They work closely with business stakeholders to understand their needs and develop solutions that meet their requirements. This course may be useful as it provides an overview of Amazon SageMaker, a platform that streamlines the process of building and deploying machine learning models.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work on various aspects of the software development lifecycle, from requirements gathering to deployment and maintenance. Those who develop software in the machine learning domain may find this course helpful as it provides an overview of Amazon SageMaker, a platform that can simplify the process of building and deploying machine learning models.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to extract meaningful insights. They work closely with business stakeholders to understand their needs and develop reports and visualizations that help them make informed decisions. Those involved in data analysis who want to learn more about machine learning may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Business Analyst
Business Analyst
Business Analysts work with business stakeholders to understand their needs and develop solutions that meet their requirements. This typically involves gathering requirements, analyzing data, and developing reports and presentations. Those interested in learning more about the use of machine learning models in a business context may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Product Manager
Product Manager
Product Managers are responsible for the development and management of software products. They work closely with engineers, designers, and other stakeholders to ensure that products meet the needs of users. Those working on machine learning based products may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze data and develop financial models. They work in various industries, including investment banking, hedge funds, and asset management. Those involved in developing quantitative models may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical methods to solve complex problems in various industries, including manufacturing, logistics, and healthcare. They work on projects such as optimizing supply chains, scheduling employees, and designing production systems. Those interested in using machine learning methods to solve operational problems may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Market Research Analyst
Market Research Analyst
Market Research Analysts conduct research to understand consumer behavior and market trends. They work on projects such as developing new products, launching marketing campaigns, and evaluating the effectiveness of advertising campaigns. Those interested in using machine learning methods to analyze market data may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and mitigate risks. They work in various industries, including finance, insurance, and healthcare. Those interested in using machine learning methods to identify and assess risks may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Financial Analyst
Financial Analyst
Financial Analysts provide financial advice to individuals and organizations. They work on projects such as evaluating investment opportunities, developing financial plans, and managing portfolios. Those interested in using machine learning methods to analyze financial data may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. They work in various industries, including insurance, finance, and healthcare. Those interested in using machine learning methods to assess risk may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work in various industries, including healthcare, education, and government. Those interested in using machine learning methods to analyze data may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. They work on projects such as extracting data from various sources, cleaning and transforming data, and loading data into data warehouses. Those interested in using machine learning methods to build data pipelines may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
Database Administrator
Database Administrator
Database Administrators design, build, and maintain databases. They work on projects such as creating database schemas, managing user access, and optimizing database performance. Those interested in using machine learning methods to manage databases may find this course helpful as it provides an overview of Amazon SageMaker, a platform used to build and deploy machine learning models.
For more career information including salaries, visit:
OpenCourser.com/course/0c823n/aws
Reading list
We've selected five 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
AWS Foundations: How Amazon SageMaker Can Help.
Provides a comprehensive overview of artificial intelligence on AWS. It covers a wide range of topics, including machine learning, deep learning, and natural language processing.
Provides a comprehensive overview of machine learning. It valuable resource for anyone who wants to learn more about machine learning and how to use it in real-world scenarios.
Provides a comprehensive overview of natural language processing. It valuable resource for anyone who wants to learn more about natural language processing and how to use it in real-world scenarios.
Provides a comprehensive overview of computer vision. It valuable resource for anyone who wants to learn more about computer vision and how to use it in real-world scenarios.
Provides a comprehensive overview of machine learning with R. It valuable resource for anyone who wants to learn more about machine learning and how to use it in real-world scenarios.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0c823n/aws
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Time
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Level
Introductory
Via
Pluralsight
Instructor
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Language
English
Good to know
Designed for learners who have experience working with machine learning but less experience working with AI
Course is industry standard and is taught by Amazon experts
Taught by AWS, an industry expert in cloud services
Offers a comprehensive study of Amazon SageMaker features and services
Develops skills and knowledge highly relevant to cloud computing
Assumes basic knowledge of machine learning
May be less suitable for learners who are complete beginners in machine learning
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