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Machine Learning
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AWS Ramp-Up Guide: Machine Learning
Built for developers and data scientists (both aspiring and current), this AWS Ramp-Up Guide offers a variety of resources to help build your knowledge of machine learning in the AWS Cloud. It features free digital training, classroom courses, videos, whitepapers, certifications, and more.
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Developer
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Data Scientist
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Data Platform Engineer
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Business Decision Maker
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Developer
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Built with the AWS Cloud. Developed for Amazon developers and engineers.
Twitch Series: AWS Power Hour Machine Learning
FundamentalLearn as AWS hosts and special guests demonstrate how to build apps with artificial intelligence (AI) services from AWS. Designed for developers without prior machine learning experience.
AWS Foundations: Machine Learning Basics
FundamentalGet an overview of the concepts, terminology, and processes in the exciting field of machine learning.
Exam Readiness: AWS Certified Machine Learning - Specialty
IntermediatePrepare for the AWS Certified Machine Learning – Specialty exam, which showcases your ability to design, implement, deploy, and maintain machine learning (ML) solutions.
The Machine Learning Pipeline
IntermediateLearn how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Explore each phase of the pipeline and apply your knowledge to complete a project.
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Data Scientist
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Build your foundation in data science and understand data readiness in the context of machine learning
The Elements of Data Science
IntermediateLearn to build and continuously improve machine learning models. Review problem formulation, exploratory data analysis, feature engineering, model training, tuning and debugging, as well as model evaluation and deployment.
Machine Learning Data Readiness
FundamentalLearn how to determine data readiness and identify when to employ it as part of your ML process. Navigate three case studies using the KNIME Analytics tool.
Practical Data Science with Amazon SageMaker
IntermediateLearn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker.
Exam Readiness: AWS Certified Machine Learning - Specialty
IntermediatePrepare for the AWS Certified Machine Learning – Specialty exam, which showcases your ability to design, implement, deploy, and maintain machine learning (ML) solutions.
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Data Platform Engineer
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Learn how architecture, data, and storage support advanced machine learning modeling and intelligence workloads
ML Building Blocks: Services and Terminology
FundamentalThese two courses clarify both the machine learning stack and the terms and processes that help you build a solid foundation in machine learning.
Machine Learning Data Readiness
FundamentalLearn how to determine data readiness and identify when to employ it as part of your ML process. Navigate three case studies using the KNIME Analytics tool.
Big Data on AWS
IntermediateLearn about cloud-based big data solutions such as Amazon Elastic MapReduce (EMR), Amazon Redshift, Amazon Kinesis, and AWS data analytics services.
Classroom | 3 days
(virtual or in person)Twitch Series: AWS Power Hour Machine Learning
FundamentalLearn as AWS hosts and special guests demonstrate how to build apps with artificial intelligence (AI) services from AWS. Designed for developers without prior machine learning experience.
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Business Decision Maker
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Demystify machine learning, artificial intelligence, and deep learning
AWS Foundations: Machine Learning Basics
FundamentalGet an overview of the concepts, terminology, and processes in the exciting field of machine learning.
Introduction to AWS Machine Learning Services
FundamentalExplore Amazon Machine Learning and Artificial Intelligence tools to enable capabilities across frameworks and infrastructure, machine learning platforms, and API-driven services.
Machine Learning for Business Challenges
FundamentalMachine learning can help you solve business problems in ways that weren't possible before—but you have to think big.
Demystifying AI/ML/DL
FundamentalAfter taking this set of courses, you’ll understand how artificial intelligence (AI) led to machine learning (ML), which then led to deep learning (DL).
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