4-Course Bundle – Machine Learning + Expert Web Applications (R-Track)

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Go from Beginner to Expert Data Scientist & Shiny Developer in Under 6-Months

Get Four of our Premium R Courses that Build Expert-Level Machine Learning Skills & Expert Web Application Skills

Learn the foundations of data science and how to apply machine learning to return business value

Taking these three courses is the equivalent of:

200+ tool-based courses

4 end-to-end projects

4 frameworks

1 foundational data science education with tidyverse

1 advanced machine learning with H2O + business consulting education

1 foundational web application education with shiny

1 advanced web application + production with shiny + AWS

Your Journey Starts Now.

Here’s what’s included.

#1. Business Analysis with R (DS4B 101-R)

A 7-week curriculum that methodically teaches the foundations of data science using R & tidyverse. You will learn:

Data Import: readr & odbc

Data Cleaning & Wrangling: dplyr & tidyr

Time Series, Text, & Categorical Data: lubridate, stringr, & forcats

Visualization: ggplot2

Functions & Iteration: purrr

Modeling & Machine Learning: parnsip (xgboost, glmnet, kernlab, broom, & more)

Business Reporting: rmarkdown

#2. Data Science For Business with R (DS4B 201-R)

A 10-week curriculum that incorporates R & H2O AutoML to use machine learning within a business problem solving framework called the BSPF. You will learn:

Getting Started: Business problem foundations, introduction to the BSPF

Business Understanding: Using dplyr & ggplot2 to size the business problem // tidy eval to build custom functions that fit within the tidyverse

Data Understanding: Use skimr and GGally packages to efficiently visualize key relationships

Data Preparation: Use recipes to prepare data in both human and machine readable formats // perform preliminary correlation analysis

H2O AutoML Modeling & Performance: Use Automated Machine Learning (AutoML) to produce 30+ models // analyze performance using ROC, Precision/Recall, Gain & Lift plots

Explaining Black-Box Models: Use LIME to explain which features are driving the complex deep learning & stacked ensemble models

Expected Value, Threshold Optimization, & Sensitivity Analysis: Link the model to financial performance through the Expected Value framework

Recommendation Algorithm Development: Use a 3-step process to develop a recommendation algorithm capable of assisting managers in retaining employees

#3. Shiny Web Applications – Level 1 (DS4B 102-R)

Here’s an example of a predictive web application that you build in this course.

New Product Prediction Application (created in this course)

Follow an Innovative 3-Part System For Learning Shiny

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.

#4. Become an Expert Shiny Developer with AWS

Expert Shiny Developer with AWS Course is an amazing course designed to teach Data Scientists and Programmers how to develop applications and deploy into production! You’ll undergo a complete transformation learning the most in-demand skills that organizations need right now. Time to accelerate your career!

Discover What’s Inside the Expert Shiny Developer with AWS Course

Crafted For Data Scientists and Programmers

That need to deploy shiny apps into production

Confidently build & deploy machine learning models for your organization

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