Ementorhub

Data Engineering in AWS

This course is part of Exam Prep MLS-C01: AWS Certified Specialty Machine Learning Specialization

Instructor: Whizlabs Instructor

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

Jupyter

Machine Learning

Feature Engineering

Data Cleansing

Data Manipulation

Dimensionality Reduction

Exploratory Data Analysis

Unsupervised Learning

Amazon Web Services

AWS SageMaker

Data Collection

Data Migration

There are 2 modules in this course

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.

Feature extraction and feature selection

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