Big Data on AWS Certification Training Course Overview

The AWS Certified Big Data - Specialty certification training is intended for individuals who perform complex Big Data investigations with at least 2 years of experience using AWS technology. Big Data is an advanced certification and its best handled by students who have already gotten associate-level certification in AWS & have some real-world industry experience.

AWS Big Data certification won't just assistance you become familiar with some new skills, it can position you for a higher paying job or help you transform your present role into a Big Data and Analytics professional.


  • Experienced technologists looking certification in Big Data technologies on Amazon Web Services.
This course prepares you for Exam BDS-C00. Download Course Contents

Big Data on AWS Course schedule & Prices

Course Details Schedule
Live Virtual Classroom (Instructor-Led)
Duration : 3 Days (6 Days for 4 Hours/Day)
Fee : 1,100 (Includes Taxes) 
9 AM - 5 PM (Flexible Time Slots for 4 hours option)

Client's Location
As per mutual convenience
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request

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Course Prerequisites

Students hold an AWS Certified Cloud Practitioner or a current Associate-level certification: AWS Certified Solutions Architect - Associate, AWS Certified Developer - Associate or AWS Certified SysOps Administrator - Associate.

What you will learn:

  • Design & Maintain Big Data.
  • Execute core AWS Big Data services according to basic architecture best practices.
  • Leverage tools to automate data analysis.
  • Store big data with S3 & DynamoDB in a scalable, and secure manner.
  • Use the Hadoop ecosystem with AWS using Elastic MapReduce.
  • Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS & Aurora.
  • Visualize big data in the cloud using AWS QuickSight.
  • Process big data with AWS Lambda & Glue ETL.
  • Move & transform massive data streams with Kinesis.