Bundle - DS For Business + Web Apps (Level 1): R-Track - Courses 101, 102, & 201
Go from Beginner to Advanced Data Science and learn distributed Web Applications in the process!
Get three of our flagship R courses that build Expert-Level Machine Learning Skills & Intermediate 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:
130+ tool-based courses
3 end-to-end projects
1 foundational data science education
1 advanced machine learning + business consulting education
1 foundational web application education
Courses Included with Purchase
Price for Bundle: $1,149
That's a savings of $148 when you purchase all 3 courses!
This course is closed for enrollment.
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.
After taking these 3 courses you will be able to confidently build expert Machine Learning Models & distribute intermediate ML-Powered Web Applications within a business
This course is closed for enrollment.
Founder of Business Science and general business & finance guru, He has worked with many clients from Fortune 500 to high-octane startups! Matt loves educating data scientists on how to apply powerful tools within their organization to yield ROI. Matt doesn't rest until he gets results (literally, he doesn't sleep so don't be suprised if he responds to your email at 4AM)!