IT Professional Certifications     Amazon     AWS Certified Machine Learning – Specialty     AWS Certified Machine Learning – Specialty

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Machine learning (ML) has become indispensable across all industries. With staggering amounts of data generated globally every second, it's impossible to make sense of it without using such advanced data analytics.
The AWS Certified Machine Learning - Specialty certification is one of the most coveted yet challenging certs a data engineer or scientist can get. To pass the associated exam, candidates must demonstrate knowledge of various machine learning concepts and the ability to solve real-world business challenges. Use this course to prepare for acquiring this valuable certification.
Get to grips with key data engineering and machine learning terminology, concepts, tools, tasks, and workflows. Then, dive into how the AWS Machine Learning platform is used for real-world applications.
Upon completing this course, you'll recognize key ML concepts and how to prepare datasets, develop ML models, and optimize models for improved predictive accuracy.

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Objectives

AWS Certified Machine Learning: Data Engineering, Machine Learning, & AWS discover the key concepts covered in this course define the basics of data engineering, its real-world applications, and the role of a data engineer describe the main stages of the data science pipeline (collect, store, transform, label, and optimize) define machine learning and list its applications in the real world define terminology used in machine learning and name typical approaches and workflows compare machine learning to other fields, like artificial intelligence, data mining, and statistics, discussing applications, limitations, and ethics describe how data repositories and data warehouses are used describe how data ingestion works and define a data pipeline describe how to transform data for processing outline the basic concept behind Amazon Web Services and describe its capabilities describe the ML capabilities of the AWS platform, various tools it offers, and example real-world applications where it can be used summarize the key concepts covered in this course