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Matt Dancho – DS4B 102-R: Shiny Dashboards
Sale page: https://university.business-science.io/p/ds4b-102-r-shiny-web-application-business-level-1
Predictive Web Applications Productionalize Data Science
A data scientist generates organizational value by building web apps that take machine learning models into production.
Here’s an example of a predictive web application that you build in this course.
This web application empowers business people to make data-driven decisions by more consistently pricing products. The application incorporates:
- Shiny – A web application framework with UI components that are reactive to user input.
- Flexdashboard – A dashboarding framework that is built on top of RMarkdown.
- parsnip and XGBoost – Machine learning models used to predict product prices.
Most importantly, business people can use the application to improve the consistency of new product prices based on an existing product portfolio thanks to the power of Machine Learning!
Your Organization Cares About Branding
So give it to them. Learn how to customize the appearance of your application to match your organizations branding.
Final Project
You will build a Sales Dashboard that:
- Uses XGBoost to Predict Sales Demand by Customers & Product Categories.
- Toggles between Light and Dark Themes – Customized by You and your theme-building skills!
- Controls flow using Reactive Programming
- Will be distributed via Shinyapps.io
Final Project
This course is designed for…
- Beginner data scientists that have completed the Data Science for Business Part 1 course and want to build predictive web applications
- Intermediate data scientists familiar with R but want to learn Shiny and Flexdashboard
Follow a 3-step learning path:
- Build your knowledge of core concepts with a Sales Dashboard
- Extend your knowledge of Machine Learning and advanced techniques into Price Prediction Application
- Customize the end product with theme and logos
Step 1: You’ll start by creating a Sales Dashboard
Creating a Sales Dashboard exposes you to reactive programming. You will apply complex rules to control how your application functions when users interact with the app.
You gain experience using:
- Shiny
- Geographic Data
- Time Series Data
- Interactive Plots
- Reactive Programming
- Observing Events & Controlling Flow
Step 2: Next, You Create A Predictive Web Application
You will build a new application that integrates Machine Learning (XGBoost) along with a more complex interactive visualization.
You learn how to:
- Integrate machine learning (parsnip and XGBoost) into a Web App
- Modularize code into functions
- Create advanced interactive charts
Step 3: You finish by Customizing Your Web Application
Your company’s brand appearance is important. Make an app theme that is consistent with the look and feel of your organization’s branding.
You will:
- Learn to use Google Inspector for inspecting web pages
- Add logos
- Adjust the theme with CSS
Business Objective: Use Data Science to More Consistently Price Products
The Business Problem:
Businesses can lose customer confidence and profitability if products are inconsistently priced.
The Solution:
This web application solves the inconsistent pricing problem by using predictive analytics to generate new product prices based on existing products.
The application is easy to use, and best of all, an app like this generates business value for your organization!
We provide you:
- A Complete Learning Path to taking you from basic knowledge of R to being able to build and deploy interactive, machine-learning powered web apps
- A Cohesive Tool Chain that includes shiny, flexdashboard, shinyWidgets, and shinyjs
- Comprehensive resources: You are provided a cheat sheet, code templates, and resources that speed up learning and make referring back to materials simple.
- Full Life-Time Access: Once you purchase the course, you gain life-time access to content now and any updates in the future.
- Access to our Private Slack Community where you can access Matt (the course instructor) and network with other students.
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