Coursera

AWS: Data Analysis and Visualization (Coursera)

Offered by Whizlabs,
AWS: Data Analysis and Visualization (Coursera)

AWS: Data Analysis and Visualization Course is the fourth course of AWS Certified Data Analytics Speciality Specialization. This course teaches Data Analysis and Visualization by exploring AWS Services such as Athena, Kinesis, QuickSight, Redshift and Kibana.

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The course is divided into three modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 4:00 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: AWS: Data Analysis and Visualization Part 1
Module 2: AWS: Data Analysis and Visualization Part 2
Module 3: AWS: Data Analysis and Visualization Part 3
Course 4 of 5 in the Exam Prep DAS-C01: AWS Certified Data Analytics Specialty Specialization.

What You Will Learn

  • Understand analysis and visualization based services
  • Design appropriate data analysis solution for a given scenario
  • Examine AWS based Visualization Services.
  • Examine AWS based Analytics Services.

Syllabus

WEEK 1
AWS: Data Analysis and Visualization Part 1
Welcome to Week 1 of the AWS: Data Analysis and Visualization.
This week, we will focus on determining the operational characteristics of an analysis and visualization solution, and analyzing AWS services such as usage patterns, performance, and cost. We will also learn how to implement Kinesis Data Analytics to analyze streaming data in real-time. Through practical demonstrations, we will gain hands-on experience with analyzing data using Kinesis Data Analytics, and learn how to effectively use AWS services for analysis and visualization needs.

WEEK 2
AWS: Data Analysis and Visualization Part 2
Welcome to Week 2 of the AWS: Data Analysis and Visualization.
This week, we will analyze various AWS services based on their durability, availability, scalability, elasticity, interfaces, and anti-patterns. We will also learn how to demonstrate AWS services visualization and describe Amazon QuickSight. By the end of the week, we should have a good understanding of how to leverage AWS services for data visualization while considering their durability, availability, scalability, elasticity, and interfaces, as well as how to use QuickSight for business intelligence needs.

WEEK 3
AWS:Data Analysis and Visualization Part 3
Welcome to Week 3 of the AWS: Data Analysis and Visualization. This week, we will focus on selecting the appropriate data analysis solution for a given scenario, and implementing various patterns using EMR, Kinesis, and Redshift. We will also learn how to implement Elasticsearch and Kibana for data visualization needs. By the end of the week, we should have a good understanding of how to leverage AWS services and patterns for data analysis and visualization needs, and how to effectively use Elasticsearch and Kibana for data visualization.

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