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Machine Lerning Engineer
Module 1: Introduction and overview of Amazon QuickSight
- What is QuickSight and what are the key features?
- Why use QuickSight for data visualization?
- Common use-cases
Module 2: Getting Started with Amazon QuickSight
- Loading data
- Visualizing data
- Demo of the QuickSight interface
- Hands-on lab: Creating your first dashboard
Module 3: Enhancing and adding interactivity to your dashboard
- Overview of techniques to enhance the usability of your dashboard
- Optimizing the size, layout, and aesthetics of a dashboard
- Adding interactivity
- Hands-on lab: Enhancing your dashboard
Module 4: Preparing data for analysis
- Working with datasets
- Data preparation and manipulation best practices
- Hands-on lab: Preparing data for analysis
- Explaining the benefits, use cases, and key features of Amazon QuickSight
- Designing, creating, and customizing QuickSight dashboards to visualize and extract business insights from your data
- Selecting and configuring appropriate visualization types to identify, explore, and drill down on business insights
- Describing how to use one-click embed to incorporate visual analytics into applications
This course comes in 2 instructor-led full day sessions with the instructor supervising the participants live. Each course consists of theory parts with live demos and practical lab exercises. The course can be attended via Zoom. Please also refer to the course description for specific details regarding the prerequisites and the covered topics.
This course is intended for the following job roles:
- Data Analytics
Participants should have at least one year of experience in business intelligence or a similar role as well as having basic knowledge in the fundmentals of data analysis.
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