Certification     Amazon     AWS Certified Machine Learning – Specialty     AWS Certified Machine Learning – Specialty

---

As the amount of data being collected has exploded, it has become crucial for businesses to rapidly access, transform, and analyze data. From the traditional batch processing to the ever-evolving real-time data analytics, AWS has various tools to handle large volumes of data and perform real-time analytics to ensure high-service uptimes and personalize recommendations.
Explore various Amazon tools like AWS Glue, AWS Data Catalog, and AWS Kinesis using this course. These tools are commonly used for data movement. This course will also help you understand how these processes function on the AWS platform and familiarize you with the data movement workflows.
Data movement and processing are at the core of any data analysis, and after completing this course, you'll be familiar with multiple tools and approaches that can be used to conveniently transform raw data, combine databases, and stream data, Further, you'll be able to prepare for the AWS Certified Machine Learning - Specialty certification.

---

---

Objectives

AWS Certified Machine Learning: Data Movement discover the key concepts covered in this course describe how AWS Glue works and list its benefits specify the capabilities of AWS ETL pipelines recognize AWS Glue's functionality define data streaming and list its use cases and benefits compare the differences between traditional batch processing and evolving stream processing describe the functionality of AWS Kinesis and outline its features and workflows describe the capabilities of working with AWS Kinesis specify how to work with video streams in AWS Kinesis specify how to work with data streams in AWS Kinesis describe how data firehouse functions in AWS Kinesis describe how to use AWS Kinesis for data analytics tasks, such as real-time alerts and actions outline the functionalities of AWS Kinesis data stream summarize the key concepts covered in this course