Build Train and Deploy Machine Learning Models with Amazon SageMaker
Amazon SageMaker provides the tools and resources needed to build, train, and deploy machine learning models, enabling developers to create REST APIs to integrate them into applications and solve real-world problems. ▼
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Course Feature
Cost:
Free Trial
Provider:
Pluralsight
Certificate:
Paid Certification
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from Pluralsight platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course provides an overview of Amazon SageMaker, a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models. Participants will learn the basics of setting up SageMaker, building and training models for image classification, deploying models as REST APIs, and managing security and scalability. Upon completion, participants will have a foundational understanding of Amazon SageMaker and the ability to create their own machine-learning-enabled applications.
[Applications]
Upon completion of this course, learners are encouraged to apply their knowledge of Amazon SageMaker to create their own machine-learning-enabled applications. Learners should consider the various real-life scenarios in which they can apply their knowledge of Amazon SageMaker to build, train, and deploy models. Additionally, learners should consider the security and scalability of their applications when using Amazon SageMaker.
[Career Paths]
1. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models. They use tools such as Amazon SageMaker to build, train, and deploy models. They also need to be able to integrate the models into applications and manage security and scalability. This role is becoming increasingly important as more companies are looking to leverage machine learning to improve their products and services.
2. Data Scientist: Data Scientists use machine learning models to analyze data and extract insights. They need to be able to understand the data, develop models, and interpret the results. They also need to be able to communicate their findings to stakeholders. This role is becoming increasingly important as companies are looking to leverage data to make better decisions.
3. AI/ML Developer: AI/ML Developers are responsible for developing applications that use machine learning models. They need to be able to understand the data, develop models, and integrate them into applications. This role is becoming increasingly important as more companies are looking to leverage AI/ML to improve their products and services.
4. Cloud Architect: Cloud Architects are responsible for designing and implementing cloud-based solutions. They need to be able to understand the data, develop models, and integrate them into cloud-based solutions. This role is becoming increasingly important as more companies are looking to leverage cloud-based solutions to improve their products and services.
[Education Paths]
1. Bachelor of Science in Computer Science: This degree path focuses on the fundamentals of computer science, including programming, software engineering, and data structures. It also covers topics such as artificial intelligence, machine learning, and natural language processing. With the increasing demand for data-driven solutions, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.
2. Master of Science in Artificial Intelligence: This degree path focuses on the development of intelligent systems and their applications. It covers topics such as machine learning, natural language processing, computer vision, and robotics. With the increasing demand for AI-driven solutions, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.
3. Master of Science in Data Science: This degree path focuses on the analysis and interpretation of large datasets. It covers topics such as data mining, machine learning, and predictive analytics. With the increasing demand for data-driven solutions, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.
4. Doctor of Philosophy in Machine Learning: This degree path focuses on the development of advanced machine learning algorithms and their applications. It covers topics such as deep learning, reinforcement learning, and natural language processing. With the increasing demand for AI-driven solutions, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.
Course Provider
Provider Pluralsight's Stats at AZClass
Pluralsight ranked 16th on the Best Medium Workplaces List.
Pluralsight ranked 20th on the Forbes Cloud 100 list of the top 100 private cloud companies in the world.
Pluralsight Ranked on the Best Workplaces for Women List for the second consecutive year.
AZ Class hope that this free trial Pluralsight course can help your Machine Learning skills no matter in career or in further education. Even if you are only slightly interested, you can take Build Train and Deploy Machine Learning Models with Amazon SageMaker course with confidence!
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Quiz
Submitted Sucessfully
1. What is the main purpose of this course?
2. What type of model is used in this course?
3. What is the real-life application of the model used in this course?
4. What is Amazon SageMaker?
Correct Answer: It is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models.
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