Use expert techniques to get the best machine learning results using the power of the DataRobot API. Build custom visualizations and autopilot processes and enhance results through sophisticated statistical methods. This course provides hands-on coverage of the DataRobot API using R to create projects, build and interpret models, and generate predictions programmatically. This course will move quickly and provide you with direct opportunities in class to test your learning and write code as it is presented in a template Jupyter notebook.
Audience: Users who want to implement R for modeling processes in DataRobot.
Prerequisite: DataRobot Essentials or DataRobot for Data Scientists, or equivalent, and experience programming in R, working with data frames and lists, and using the Tidyverse collection of R packages.
Requirements: Please read the installation instructions in the Resources section.
Completion: Attendance at all instructor-led sessions is required for course completion. These sessions must be taken in the order listed.
Please use this time zone conversion tool to find a session that works best for your schedule and time zone: worldtimebuddy.com
PDT: Americas/Pacific EDT: Americas/Eastern BST: Europe/London SGT: Asia/Singapore
AEST: Australia/Eastern
Note: To ensure participants are properly configured and enabled across our internal systems, session registration closes 2 business days prior to the start of the session.
| Instructor-led Session | Date | Spaces left |
|---|---|---|
| Modeling Basics with the API | 20 |
| Instructor-led Session | Date | Spaces left |
|---|---|---|
| Model Interpretation, Understanding, and Deployment with the API | 20 |
