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
Data Engineering in AWS
This course is part of Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
Instructor: Whizlabs Instructor
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Gain insight into a topic and learn the fundamentals.
3.7
(19 reviews)
Beginner level
Recommended experience
5 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
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
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
7 assignments
Taught in English
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This course is part of the Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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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
12 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
11 videos4 readings5 assignments
Instructor
Offered by
Recommended if you're interested in Machine Learning
Whizlabs
Amazon Web Services
Duke University
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Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
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