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.
Data Engineering in AWS
This course is part of Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Instructor: Whizlabs Instructor
Sponsored by ITC-Infotech
3,542 already enrolled
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What you'll learn
Analyze various data gathering techniques
Analyze techniques to handle missing data
Implement feature extraction and feature selection with Principal Component Analysis and Variance Thresholds
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7 assignments
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There are 2 modules in this course
Welcome to Week 1 of Data Engineering in AWS Course. This week will begin with understanding SageMaker Jupyter Notebooks setup. We’ll also get an overview of handling and dropping Missing Data.This week will end by analyzing information about Gathering data.
What's included
9 videos2 readings2 assignments1 discussion prompt
Welcome to Week 2 of Data Engineering in AWS Course. This week , we’ll learn to perform Feature extraction and feature selection with Principal Component Analysis and Variance Thresholds. We’ll also explore feature extraction and feature selection techniques. By the end of this week, we’ll analyze AWS Migration services and tools.
What's included
9 videos4 readings5 assignments
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