English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 1h 38m | 269 MB
Holistic solutions to visualization problems you can implement in any other visualization tool!
With businesses understanding and valuing their data more and more these days, their requirements turn complex one step at a time, which may lead to several roadblocks when plotting those visualizations. These minor blocks can be frustrating as there are little or no solutions available online.
After finishing this course, you’ll be able to easily maneuver through common issues. We’ll also go through some complex problems you may face, so you are always prepared with a solution for visualization at work. We’ll cover problems and solutions in Tableau (the best visualization tool as ranked by the Gartner report 2017). In this course, our aim is to provide a solution to the visualization problem so that you can implement if needed in any other visualization tool too.
This is a comprehensive course that covers complex visualization problems and functionalities that existing visualization tools like Tableau and R can offer. This course is divided into clear chunks, so you can learn at your own pace and focus on your own area of interest.
What You Will Learn
- Build apps in popular R packages such as Shiny
- Get industry best practices for data visualization
- Get comfortable with performing calculations in your visualization
- Overcome common problems with loading data and maintaining live connections
- Deploy your machine learning visualization outputs directly to a web page
- Understand the importance of placement and sorting of graphs
- Perform complex calculations in the visualization itself
- Implement forecasting capabilities from the visualization platform itself
- Optimize visualizations to get a faster load
01 The Course Overview
02 Being Specific with the Data You Need
03 Letвs Find Mistakes to Not Make Them
04 Presentation Ready Dashboards
05 Empowering Our Audience
06 Creating Sets
07 Creating Parameters
08 Creating Calculated Fields
09 Example of Top 10 with Ranks
10 Creating Time Series and Adding Forecasting Models
11 Understand What We Need to Build
12 Finalizing GUI and What We Will Display
13 Creating an R Shiny GUI Dashboard that You Can Reuse Easily Elsewhere
14 Handling Data
15 Passing Data to Functions
16 Creating a Model and Passing Output to R Shiny GUI
17 Overview and Summary
18 Mini Project