SDS Bootcamp and Training Courses

DATACAMP

Plans and Pricing - Choose a Package | DataCamp

The School of Data Science and College of Computing and Informatics launched a new partnership with DataCamp in 2022. DataCamp is an online learning platform that focuses on teaching students the comprehensive skills they need to become successful data scientists. The platform provides a fun and interactive way to master the foundation and learn advanced-level coding skills. DataCamp will help you keep you fluent in the language of data. All SDS students actively enrolled in classes, and all SDS faculty and staff, have FREE access to the full suite of training modules, and access to learning resources on hundreds of topics in the field of data science. Looking for a convenient review of SQL? An overview of Tableau techniques? An introduction to PowerBI?

Accessing DataCamp’s Full Library

Follow these directions to gain access to DataCamp’s full library and the custom SDS tracks.

  1. Create a free DataCamp account using your @charlotte.edu email.
  2. Request access to DataCamp by submitting this form or clicking the button below.
  3. Look for an email from DataCamp inviting you to join the UNC Charlotte group and follow the instructions.

Custom Tracks for SDS Students

The SDS faculty have collaborated to create two custom tracks, SDS R Bootcamp and SDS Python Bootcamp, on DataCamp. Follow these directions to enroll:

  1. Log in to DataCamp using your registered university email id.
  2. Go to Learn —> Tracks —> Organization Tracks.
  3. Select your preferred custom track.

Upon completion of each Custom Track/Bootcamp, students will receive a statement of accomplishment to demonstrate their readiness for the courses.


SDS BOOTCAMP COURSES

SDS Training Bootcamps

In addition to DataCamp, the School of Data Science has also created some “in-house” training modules in Canvas. These courses are online, asynchronous, and available to all SDS students. Spring 2024 sessions are currently open for students actively enrolled in SDS graduate and undergraduate courses.

COURSE DESCRIPTIONS

  • Introduction to SAS For Data Science: This course provides a rudimentary introduction to programming in SAS. It covers SAS libraries, datasets, variables, data import, and additional SAS training materials.
  • Overview of Statistics for Data Science: This is a self-paced course intended to provide a review of foundational statistics methods necessary for success in data science and health informatics programs. It covers the basics of statistics, probability, probability distributions, descriptive statistics, and hypothesis testing.

COURSE REQUIREMENTS

Each course is designed to be completed within four weeks or less. Upon successful completion of each course, students will receive a statement of accomplishment in the form of a PDF badge, which will be shared via email. These badges can be presented in future courses to demonstrate completion and avoid retaking a boot camp course.