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Data Engineering in AWS
  • Level Foundation
  • Duration 4 hours
  • Course by Whizlabs
  • Offered by

About

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

Modules

Introducing Data Garthering Techniques

    • 12 Videos
    • 2 Readings
    • 1 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Introducing Data Gathering Techniques-Knowledge Check
  • Week 1 Assessment

1 Discussions

  • Meet and Greet

12 Videos

  • Welcome to the AWS Machine Learning Specialty Certification Exam course
  • Overview of the exam
  • Goals of the course
  • Machine Learning Terminology - Categories
  • Machine Learning Terminology - Data Engineering-Advanced
  • Introduction to Machine Learning Cycle
  • Machine Learning Cycle - Continued
  • How to Setup Amazon Sagemaker Environment?
  • Gathering data
  • Handling Missing Data - Overview and Drop Technique
  • Handling Missing Data - Other Imputation Techniques-Part 1
  • Handling Missing Data - Other Imputation Techniques-Part 2

2 Readings

  • Course Outline
  • Introduction to Data Engineering Overview

Feature extraction, feature selection with Principal Component Analysis and Variance Thresholds

    • 3 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Feature extraction, Feature Selection with Principal Component Analysis and Variance Thresholds - Knowledge Test

3 Videos

  • Feature extraction and feature selection with Principal Component Analysis and Variance Thresholds
  • Feature Extraction and Selection - Lab Part 1
  • Feature Extraction and Selection - Lab Part 2

1 Readings

  • Feature extraction and feature selection Overview

Other Features

    • 8 Videos
    • 3 Readings
    • 4 Assignment
Show info about module content

4 Assignment

  • Other Features - Knowledge Test
  • Week 2 Assessment
  • Overall Course Assessment Quiz
  • Project: Perform ETL operation in Glue with S3

8 Videos

  • Encoding categorical values-Part 1
  • Encoding categorical values-Part 2
  • Numerical engineering-Part 1
  • Numerical engineering-Part 2
  • Text feature editing
  • Amazon Mechanical Turk
  • AWS Migration services and tools
  • Exam tips

3 Readings

  • Key Takeaways of the course
  • Project Resource: glue_code.py
  • Project Resource: Sample Data

Auto Summary

"Data Engineering in AWS" is a foundational course in the AWS Certified Machine Learning Specialty specialization, offered by Coursera. It spans 240 minutes of engaging video lectures and quizzes, providing both theoretical and hands-on knowledge. The course covers data gathering techniques, missing data handling, feature extraction, and selection. Ideal for individuals with two years of ML experience in AWS, the course is available through Starter and Professional subscription plans, and is perfect for those looking to deepen their data engineering skills in AWS.

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