AWS Academy Data Analytics Course

  • Formats:

    Live Online


  • Duration:

    7.5 hours

  • Registration Fee:


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Start Date

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Part-Time: Coming again in 2023

AWS Academy

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Data Analytics Course: Overview

Ashton College’s AWS Academy Data Analytics course is a series of lab exercises that teach students how to conduct Big Data analysis with practical, real-world examples. Students will learn how to analyze extremely large data sets, and to create visual representations of that data, using a case-study approach. The labs and learning resources are designed to supplement an institution’s existing Big Data and data analytics courses and provide students with hands-on experience working with data at scale. Geared toward students interested in pursuing careers in data analysis, AWS Academy Data Analytics requires a strong foundation in IT concepts and skills, and it contains seven-and-a-half hours of content.

Check out our other AWS Academy courses: Certified Cloud PractitionerSolutions Architect – Associate, Developer – Associate, SysOps Administrator – Associate and Machine Learning Foundations.


AWS Academy Data Analytics requires a strong foundation in IT concepts and skills, such as those that students gain through the AWS Academy Cloud Foundations course. Students may benefit from completing the free AWS Data Analytics Fundamentals online training. Before taking this intermediate course, students should be able to:

  • Describe the difference between an online transaction processing (OLTP) system and an online analytical processing (OLAP) system
  • Describe the differences between a database and a data warehouse
  • Design a set of data objects and table relations for a simple data set
  • Write simple data retrieval and manipulation queries with SQL
  • Describe the five V's of big data (Velocity, Volume, Value, Variety, and Veracity)
  • List common use cases and domains for big data solutions
  • Normalize database design

Students are not expected to have programming experience.

Learning Objectives

Upon completion of this course, the successful student will have reliably demonstrated the ability to:

  • Describe big data analytical concepts
  • Ingest, store, and secure data
  • Query a data store with manual schema specification
  • Query a data store with automated schema generation
  • Load and query data in a data warehouse
  • Visualize structured and unstructured data
  • Automate loading data into a data warehouse
  • Analyze unstructured data
  • Analyze IoT data

Topics Covered

Lab 1: Ingesting Data in Amazon S3

Lab 2: Querying Amazon S3 Data Using Amazon Athena

Lab 3: Transforming Data Using Amazon S3, AWS Glue, and Amazon Athena

Lab 4: Loading the Amazon Redshift Cluster with Data and Querying

Lab 5: Delivering Insights using Amazon QuickSight

Lab 6: Setting Up and Executing a Data Pipeline Job to Load Data into Amazon S3

Lab 7: Streaming Data with AWS Kinesis Firehose, Amazon Elasticsearch, and Kibana

Lab 8: Using AWS IoT Analytics for Data Ingestion and Analysis


Subject to change without notice

Richard Spencer

Richard SpencerRichard Spencer has worn many hats during his time in the IT industry over the last 15 years. Starting his career in the telecommunications field, Richard is now a full-time information technology instructor. Richard has successfully attained his Cisco Certified Network Associate (CCNA) certification, CCNA “Train the Trainer” certification, and three certifications from Amazon Web Services: Solutions Architect Associate, Sysops Administrator, and DevOps associate. His professional expertise and interest align with all things AWS and networking.



Roman Mirakhmedov


Roman Mirakhmedov holds a Master’s in Applied Mathematics and Computer Science from Lomonosov Moscow State University and is a Ph. D. candidate in Artificial Intelligence. He loves building next-generation cloud-native solutions to help generate maximum value from the cloud. Roman is an AWS Academy Accredited Educator for Cloud Foundations, Cloud Architecture, SysOps, DevOps and Machine Learning. He is one of the very few people to hold all AWS certifications. He teaches cloud, machine learning, artificial intelligence, software development and applied mathematics. He is also a Senior Director, a Cloud Consulting with Prodapt Solutions, and a global system integrator.


Live Online


  • Coming again in 2023
    • Students must devote at least 2.5 hours per week to attend live webinars
    • Webinars will be held on Mondays from 5:00 to 7:30 pm PST
    • Outside of live instructional periods, students will be expected to take part in various independent and/or group activities


Registration fee for this course is $225.

Technical Requirements

Live Online Students

Ashton College uses web conferencing tools for conducting online classes and online learning management systems for managing resources, assignments, and grades. These tools help instructors and students connect live online as well as asynchronously. The basic requirements for online learning include a computer, webcam, speakers, and a microphone or a headset and headphones, along with a reliable internet connection. Though online learning can be pursued using smartphones and tablets, the use of laptops or desktop computers is encouraged for an enhanced learning experience.


This course does not require approval by the Private Training Institutions Branch of the Ministry of Advanced Education, Skills & Training. As such, it was not reviewed.

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