Data Engineering in AWS

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Course Overview

Data Engineering in AWS is the first course in the AWS Certified Machine Learning Specialty specialization. This course helps learners to analyze various data gathering techniques. They will also gain insight to handle missing data. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:30-3:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners. Module 1: Introduction to Data Engineering Module 2: Feature extraction and feature selection Candidate should have at least two years of hands-on experience architecting, and running ML workloads in the AWS Cloud. One should have basic ML algorithms knowledge. By the end of this course, a learner will be able to: - Understand various data-gathering techniques - Analyze techniques to handle missing data - Implement feature extraction and feature selection with Principal Component Analysis and Variance Thresholds.

Course FAQs

What are the prerequisites for 'Data Engineering in AWS'?

Prerequisites for this continuing education class are set by Whizlabs. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.

Will I receive a certificate for this CE class?

Yes, upon successful completion, Whizlabs typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.

How long does this online course take to complete?

Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.