Getting Started with Data Analytics on AWS (Coursera)

Offered by AWS,
Getting Started with Data Analytics on AWS (Coursera)

With the explosion of data collection enabled by the internet, mobile applications and transformation into the cloud, effective data analytics is turning into a critical tool in practically every domain – from academia to enterprise. In this course, learners will get an introduction to the different types of data analytics (descriptive, diagnostic, predictive and prescriptive) and dive into the basics of descriptive data analysis using data and tools in the AWS Cloud.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Examples of common data analysis scenarios and benefits of doing analytics in the cloud will be discussed. Services such as Amazon S3, Amazon Athena, AWS Cloudtrail, AWS Datasets and Amazon Quicksight will be introduced with an objective to build a security dashboard that could lead to insights or further exploration.

Syllabus

WEEK 1: Getting Started with Data Analytics on AWS

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Business Analytics with R (Coursera) Coursera
University of Illinois at Urbana-Champaign

Introduction to Business Analytics with R (Coursera)

Nearly every aspect of business is affected by data analytics. There are many powerful tools that can quickly process large amounts of data. For businesses to capitalize on data analytics, they need leaders who understand the data analytic process. Even more valuable are leaders who know how to analyze big data. This course addresses the human skills gap by providing a foundational set of data analytic skills that can be applied to many business settings.

Jun 22nd 2026
4 Weeks
Python Data Analytics (Coursera) Coursera
Meta

Python Data Analytics (Coursera)

This course introduces the use of the Python programming language to manipulate datasets as an alternative to spreadsheets. You will follow the OSEMN framework of data analysis to pull, clean, manipulate, and interpret data all while learning foundational programming principles and basic Python functions. You will be introduced to the Python library, Pandas, and how you can use it to obtain, scrub, explore, and visualize data.

Jun 22nd 2026
4 Weeks
Digital Manufacturing & Design (Coursera) Coursera
University at Buffalo,The State University of New York

Digital Manufacturing & Design (Coursera)

This course will expose you to the transformation taking place, throughout the world, in the way that products are being designed and manufactured. The transformation is happening through digital manufacturing and design (DM&D) – a shift from paper-based processes to digital processes in the manufacturing industry. By the end of this course, you’ll understand what DMD is and how it is impacting careers, practices and processes in companies both large and small.

Jun 22nd 2026
2 Weeks
Communicating Business Analytics Results (Coursera) Coursera
University of Colorado Boulder

Communicating Business Analytics Results (Coursera)

The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions.

Jun 22nd 2026
4 Weeks
Politics and Ethics of Data Analytics in the Public Sector (Coursera) Coursera
University of Michigan

Politics and Ethics of Data Analytics in the Public Sector (Coursera)

Deepen your understanding of the power and politics of data in the public sector, including how values — in addition to data and evidence — are always part of public sector decision-making. In this course, you will explore common ethical challenges associated with data, data analytics, and randomized controlled trials in the public sector. You will also navigate and understand the ethical issues related to data systems and data analysis by understanding frameworks, codes of ethics, and professional guidelines.

Jun 22nd 2026
3 Weeks